Comparison between two groups’ high skepticism auditors and low skepticism auditors| Statswork

Comparison between two groups’ high skepticism auditors and low skepticism auditors, and the impact of those groups in overall assessment of fraud risk Statisticalpeerreview Statisticalpeerreview This Assignment has been completed by statswork © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com Copyright © statswork. All rights reserved. 0 www.statswork.com

Statisticalpeerreview ` Table of Contents Introduction ................................................................................................................................. 6 Test for Normality ....................................................................................................................... 6 Multi-Collinearity...................................................................................................................... 13 Common Method Variance (CMV) .......................................................................................... 15 Reliability .................................................................................................................................. 23 Independent sample t-test .......................................................................................................... 27 Analysis of Variance (ANOVA) ............................................................................................... 28 Chi-square tests ......................................................................................................................... 31 Correlation ................................................................................................................................. 33 Information ................................................................................................................................ 35 Analysis of Variance (ANOVA) ............................................................................................... 41 Correlation ................................................................................................................................. 43 Regression ................................................................................................................................. 48 References ................................................................................................................................. 56 1 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Table of Contents Table 6: Frequency for highest level of education........................................................................ 20 Table 7: Frequency for professional position ............................................................................... 21 Table 8: Frequency for professional certificate ............................................................................ 22 Table 9: Descriptive statistics for experience ............................................................................... 23 Table 10: Reliability analysis for Skepticism dimensions ............................................................ 24 Table 11: Ranking for Skepticism dimension - Self determing .................................................... 24 Table 12: Ranking for Skepticism dimension - Curiosity ............................................................ 25 Table 13: Ranking for Skepticism dimension – Self confidence .................................................. 25 Table 14: Ranking for Skepticism dimension – Interpersonal skills ............................................ 26 Table 15: Ranking for Skepticism dimension – Delibrating ........................................................ 26 Table 16: Ranking for Skepticism dimension – Questioning skills .............................................. 27 Table 17: Mean difference in skepticism dimensions between gender ........................................ 28 Table 18: Mean difference in skepticism dimensions between experience .................................. 29 Table 19: Mean difference in skepticism dimensions between level of education....................... 30 Table 20: Mean difference in skepticism dimensions between professional position .................. 31 Table 21: Association between level of skepticism and gender ................................................... 32 Table 22: Association between level of skepticism and experience ............................................. 32 Table 23: Association between level of skepticism and level of education ................................. 33 Table 24: Association between level of skepticism and professional position ............................. 33 Table 25: Correlation between skepticism dimensions ................................................................ 34 Table 26: Descriptive statistics for financial ratios in High and Low risk information ............... 35 Table 27: Descriptive statistics for perception in High and Low risk information ...................... 36 Table 28: Descriptive statistics for judgment in High and Low risk information ........................ 37 Table 29: Descriptive statistics for decision in High and Low risk information .......................... 38 2 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Table 30: Reliability analysis for fraud risk (Low and High) factors in High and low risk ......... 39 Table 31: Mean difference in fraud risk (High and low) factors between gender ....................... 40 Table 32: Mean difference in fraud risk (High and low) factors between experience ................. 41 Table 33: Mean difference in fraud risk (High and low) factors between level of education ...... 42 Table 34: Mean difference in fraud risk (High and low) factors between professional position . 42 Table 35: Correlation between fraud risk factors ......................................................................... 43 Table 36: Reliability and validity estimates for information, perception and judgment ....... Error! Bookmark not defined. Table 37: Discriminant validity ..................................................... Error! Bookmark not defined. Table 38: Pathways coefficients for Information, Perception and JudgmentError! Bookmark not defined. Table 39: Reliability and validity estimates for information, perception, judgment and Decision ....................................................................................................................................................... 45 Table 40: Discriminant validity .................................................................................................... 46 Table 41: Pathways coefficients for Information, Perception, Judgment and Decision ............... 46 Table 42: Reliability and validity estimates for information, judgment and Decision .......... Error! Bookmark not defined. Table 43: Discriminant validity ..................................................... Error! Bookmark not defined. Table 44: Pathways coefficients for Information, Judgment and DecisionError! Bookmark not defined. Table 45: Reliability and validity estimates for perception and DecisionError! Bookmark not defined. Table 46: Discriminant validity ..................................................... Error! Bookmark not defined. Table 47: Pathways coefficients for Perception and Decision....... Error! Bookmark not defined. Table 48: Reliability and validity estimates for perception, judgment and Decision ............ Error! Bookmark not defined. Table 49: Discriminant validity ..................................................... Error! Bookmark not defined. Table 50: Pathways coefficients for Perception, Judgment and DecisionError! Bookmark not defined. Table 51: Reliability and validity estimates for perception, judgment and Decision ............ Error! Bookmark not defined. 3 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Table 52: Discriminant validity ..................................................... Error! Bookmark not defined. Table 53: Pathways coefficients for Perception, Judgment and DecisionError! Bookmark not defined. Table 54: Reliability and validity estimates for perception, judgment and Decision ............ Error! Bookmark not defined. Table 55: Discriminant validity ..................................................... Error! Bookmark not defined. Table 56: Pathways coefficients for Perception, Judgment and DecisionError! Bookmark not defined. Table 57: Correlation between high risk incentive, opportunity, attitude and overall risk decision ....................................................................................................................................................... 47 Table 58: Correlation between low risk incentive, opportunity, attitude and overall risk decision ....................................................................................................................................................... 48 Table 59: Association between high risk incentive, opportunity and attitude on overall risk decision ......................................................................................................................................... 49 Table 60: Association between low risk incentive, opportunity and attitude on overall risk decision ......................................................................................................................................... 50 Table 61: Mean difference in fraud risk factors between level of skepticism .............................. 51 Table 62: Mean difference in high fraud risk factors in low and high risk condition between level of skepticism ................................................................................................................................. 51 4 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` List of Figures Figure 1: Percentage for gender .................................................................................................... 19 Figure 2: Percentage for full time audit experience ...................................................................... 20 Figure 3: Percentage for highest level of education ...................................................................... 21 Figure 4: Percentage for Professional Position ............................................................................. 22 Figure 5: Percentage for Professional Certificate ......................................................................... 22 Figure 6: Scatter diagram for skepticism dimensions ................................................................... 35 Figure 7: Scatter diagram for high risk perception, judgment and decision ................................. 44 Figure 8: Scatter diagram for low risk perception, judgment and decision .................................. 44 5 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Introduction In this chapter the analysis performed are test for normality, Multi-Collinearity, reliability analysis, percentage analysis, descriptive statistics, t-test, analysis of variance, chi-square test, correlation, regression analysis and partial least square (PLS) using the software SPSS 20.0. The sample size taken for the study is N=42. Test for Normality An assessment of the normality of data is a prerequisite for many statistical tests because interested in the Tests of Normality table and the Histogram our numerical and graphical methods to test for the normality of data, respectively. When a histogram’s shape approximates a bell-curve it suggests that the data may have come for a normal population. Histogram 6 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` 7 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Tests of Normality Adversely Ineffective Inadequate Recurring Rapid growth 0.141 Complex Aggressive Incentive Opportunity Attitude Overall risk Bolded value represents p>0.05 0.161 0.151 0.171 0.128 42 42 42 42 42 42 42 42 42 42 42 0.008 0.017 0.004 0.083 0.036 0.081 0.138 0.000 0.076 0.089 0.002 0.971 0.963 0.952 0.967 0.973 0.952 0.967 0.959 0.963 0.975 0.962 42 42 42 42 42 42 42 42 42 42 42 0.370 0.184 0.076 0.261 0.424 0.079 0.267 0.136 0.195 0.494 0.180 0.128 0.120 0.195 0.129 0.126 0.176 The above table presents the results from two well-known tests of normality, namely the Kolmogorov-Smirnov Test and the Shapiro-Wilk Test. The Shapiro-Wilk Test is more appropriate for small sample sizes (< 50 samples), but can also handle sample sizes as large as 2000. From the above table for the "Domination", "Adversely", “Inefective”, “Inadequate”, “Recurring”, “Rapid growth”, “Complex”, “Aggressive”, “Incentive”, “Opportunity”, “Attitude”, and "Overall risk" variables was normally distributed. If the Sig. value of the Shapiro-Wilk Test is greater than 0.05, the data is normal. If it is below 0.05, “Personal” variable the data significantly deviate from a normal distribution. Multi-Collinearity Multicollinearity is a high degree of correlation (linear dependency) among several is full ranked, making OLS impossible. When a model is not full ranked, that is, the inverse of X cannot be defined, there can be an infinite number of least squares solutions. 13 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` There is no clear-cut criterion for evaluating multicollinearity of linear regression models. condition number. However, there is no formal criterion for determining the bottom line of the tolerance R2 be considered determining significance of multicollinearity. Klein (1962) suggests alternative criterion that R2k exceeds R2 of the regression model. In this vein, if VIF is greater than 1/(1-R2) value is less than (1-R2) Table 1: Tests of Multi-Collinearity Unstandardized Coefficients Beta 0.767 Collinearity Statistics Tolerance VIF Model t-value p-value S.E 0.729 0.111 0.094 (Constant) Perception-High risk 0.467 Judgment Dependent Variable: Decision, **p<0.01 1.053 4.193 5.339 0.299 0.000** 0.727 0.000** 0.727 1 1.375 1.375 0.500 Table 1 presents the regression analysis for high risk in which dependent variable is decision and independent variables ate perception and judgment, from which multicollinearity is tested based on tolerance and VIF value. If the tolerance value less than .1 or VIF greater than 10 roughly indicates significant multicollinearity. In the above table tolerance value is 0.7 greater than 0.1 or VIF 1.4 which is less than 10. Unstandardized Coefficients Beta 0.224 0.394 0.478 Collinearity Statistics Tolerance VIF Model t-value p-value S.E 0.370 0.106 0.123 (Constant) Perception-Low risk Judgment Dependent Variable: Decision, **p<0.01 0.604 3.717 3.900 0.549 0.001** 0.513 0.000** 0.513 1 1.950 1.950 14 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Table 1 presents the regression analysis from which multicollinearity is tested based on VIF 2.0 which is less than 10. Common Method Variance (CMV) 15 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Harman single factor test using factor analysis Total Variance Explained Component Initial Eigenvalues Total % of Variance Cumulative % Total % of Variance Cumulative % 1 5.066 38.972 38.972 2 1.632 12.556 51.528 3 1.385 10.653 62.181 4 .976 7.510 69.691 5 .865 6.657 76.348 6 .709 5.455 81.803 7 .650 5.002 86.805 8 .490 3.766 90.571 9 .409 3.150 93.721 10 .311 2.394 96.115 11 .198 1.524 97.639 12 .170 1.311 98.951 13 .136 1.049 100.000 Extraction Method: Principal Component Analysis. Extraction Sums of Squared Loadings 5.066 38.972 1.632 12.556 1.385 10.653 38.972 51.528 62.181 16 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` There are another way of testing common method bias in PLS see the link below: https://www.youtube.com/watch?v=pUKT-QvQYhM Please if you could perform this test I will be thankful it is very ease method I need to get attractive results in this method as my supervisor is giving me tough time because of this. Table 2: CFA for First-order Model for fraud risk factors (Perception, Judgment and Decision) Unstandardized coefficient 1.000 1.141 -.048 .797 -22.365 1.000 .917 .498 .510 1.062 1.062 .879 1.062 1.062 1.062 1.143 1.062 1.062 Standardized coefficient .128 .101 -.004 .090 Variables S.E P-value per5 <--- perception per4 <--- perception per3 <--- perception per2 <--- perception per1 <--- perception jud4 <--- judgment jud3 <--- judgment jud2 <--- judgment jud1 <--- judgment per1 <--- Common_factor per2 <--- Common_factor per3 <--- Common_factor per4 <--- Common_factor per5 <--- Common_factor jud1 <--- Common_factor jud2 <--- Common_factor jud3 <--- Common_factor jud4 <--- Common_factor dec4 <--- marker_(decision) 1.000 dec3 <--- marker_(decision) 1.165 dec2 <--- marker_(decision) 2.254 dec1 <--- marker_(decision) -.115 dec1 <--- Common_factor dec2 <--- Common_factor dec3 <--- Common_factor dec4 <--- Common_factor Note: 1. ** Denotes significant at 1% level, NS- Not Significant .511 .623 .355 98.050 -2.610 .293 .236 .210 .124 .124 .355 .124 .124 .124 .269 .124 .124 .691 1.287 .703 .124 .124 .124 .124 0.026 0.939 (NS) 0.025 0.820 (NS) 0.002 0.035 0.015 *** *** 0.013 *** *** *** *** *** *** 0.092 (NS) 0.080 (NS) 0.870 (NS) *** *** *** *** .452 .337 .214 .238 .682 .660 .395 .517 .748 .594 .586 .467 .574 .151 .160 .248 -.016 .683 .536 .672 .738 1.062 1.062 1.062 1.062 17 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` to identify the degree to which the implicit matrix of co variances, (based on the hypothesized model), and the sample covariance matrix, based on data it seems to fit (Bollen, 1989).The structural model, 2(59)= 98.712, GFI the quality of ft was not acceptable representation of the sample data (χ (Goodness of Fit Index)=0.779; AGFI (Adjusted Goodness of Fit Index) = 0.659 which is smaller than the 0.90 criteria as suggested by Hu and Bentler (1999) and Joreskog and Sorbom (1981). Similarly, CFI=0.796, RMSEA (Root Mean Square Error of Approximation) =0.128 and RMR (Root Mean Square Residuals) =0.501, values are greater than 0.05 critical value (Steiger, 1989). Table 3: Model fit indices for first order model constructs of fraud risk factors Indices p-value CMIN/DF GFI AGFI CFI RMR RMSEA Suggested value >0.05 <5.0 >0.90 >0.90 >0.90 <0.05 <0.05 Model Fit Indices 0.001 1.67 0.779 0.659 0.796 0.501 0.128 Table 4: Frequency for Gender Gender Male Female Total Frequency (n) 26 16 42 Percentage (%) 61.9 38.1 100.0 Table 2 presents the respondents’ gender. Of total 42 respondents’ majority (62%) of them are male and 38 percent of them are female. 18 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Figure 1: Percentage for gender 38% Male 62% Female Table 5: Frequency for full time audit experience Full time audit experience (years) <=2.5 2.6-5.0 5.1-17.0 >=17.1 Total Frequency (n) 11 12 9 10 42 Mean Percentage (%) 26.2 28.6 21.4 23.8 100.0 Range (Max-Min) Full time audit experience (years) 11.7 45 (45-0) Max- Maximum, Min-Minimum Table 3 shows the full time audit experience. Majority (29%) of them with 2.6-5.0 years’ experience followed by 26 percent with less than 2.5 years and least with 21 percent with 5.1- 19 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` 17.0 years’ experience respectively. The mean of full time audit experience is 11.7 years with maximum 45 years. Figure 2: Percentage for full time audit experience 35 28.6 30 26.2 23.8 25 21.4 Percentage 20 15 10 5 0 2.6-5.0 <=2.5 >=17.1 5.1-17.0 Full time audit experience (years) Table 6: Frequency for highest level of education Highest level of education Bachelors Masters Others Total Frequency (n) 10 14 18 42 Percentage (%) 23.8 33.3 42.9 100.0 Table 4 reveals the highest level of education. Majority (43%) of them are rest of graduation followed by 33 percent with masters’ level and 24 percent with Bachelors level. 20 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Figure 3: Percentage for highest level of education 45 40 35 42.9 30 Percentage 33.3 Others 25 20 Masters 23.8 15 Bachelors 10 5 0 Others Highest level of education Masters Bachelors Table 7: Frequency for professional position Professional position Staff Senior Supervisor Manager Partner Others Total Frequency (n) 7 9 3 9 8 6 42 Percentage (%) 16.7 21.4 7.1 21.4 19.0 14.3 100.0 Table 5 shows the professional position. Majorities (21%) of them are senior and manager followed by 19 percent are partner, 17 percent are staff and least 7 percent of them are supervisor. 21 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Figure 4: Percentage for Professional Position Supervisor 7.1 Professional Position Others 14.3 Senior Staff 16.7 Manager Partner Partner 19 Staff Manager 21.4 Others Senior 21.4 Supervisor 0 10 Percentage 20 30 Table 8: Frequency for professional certificate Professional certificate ACCA CFA Others Total Frequency (n) 21 3 18 42 Percentage (%) 50.0 7.1 42.9 100.0 Table 6 reveals the professional certificate. Majority (50%) of them have ACCA certificate followed by 43 percent have rest of certificate and 7 percent have CFA certificate. Figure 5: Percentage for Professional Certificate 50 50 40 42.9 Percentage 30 ACCA Others 20 CFA 10 7.1 0 ACCA Others CFA Professional Certifcate 22 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Table 9: Descriptive statistics for experience Experience in assessing the fraud risk (in months) 27.62 Number of audit engagement experienced material fraud was discovered Experience working as an auditor (in years) Max- Maximum, Min-Minimum Mean Range (Max-Min) 480 (480-0) 4.95 150 (150-0) 11.36 42 (42-0) Table 7 presents the descriptive statistics for experience. The mean experience in assessing the fraud risk is 28 months with maximum of 480 months. The average number of audit engagement experienced material fraud was discovered is 5 with maximum of 150 audit engagement.The mean experience working as an auditor is 11 years with maximum 42 years. Reliability The internal consistency of data is checked through cronbach’s alpha (α) value. Cronbach’s alpha value is one of the measurements in reliability analysis. There is a relation between cronbach’s alpha and corr elation. Cronbach’s alpha generally increases when the correlation among the item increase. Based on the Cronbach’s alpha value, we concluded the following about the data: ?If α ≥ 0.9 – Excellent ?If 0.7 ≤ α < 0.9 – Good ?If 0.6 ≤ α < 0.7 – Acceptable ?If 0.5 ≤ α < 0.6 –Poor ?If α < 0.5 - Unacceptable 23 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Table 10: Reliability analysis for Skepticism dimensions Cronbach’s alpha Skepticism dimensions Number Range (Max-Min) 2.40 (3.40-1.00) 0.627 2.80 (6.00-3.20) 0.913 1.60 (5.00-3.40) 0.885 1.80 (4.60-2.80) 0.679 2.20 (5.80-3.60) 0.570 2.60 (6.00-3.40) 0.525 of items Mean 5 5 5 5 5 5 S.D Self determing Curiosity Self confidence Interpersonal skills Delibrating Questioning skills S.D- Standard Deviation; Max- Maximum, Min-Minimum 2.27 4.87 4.26 3.85 4.90 4.59 0.65 0.76 0.47 0.39 0.56 0.59 Table 8 presents the descriptive statistics for each dimensions and the reliability analysis outcome using the Cronbach’s alpha method in order to measure the reliability of each multi- item of Skepticism dimensions (i.e. Self determing, Curiosity, Self-confidence, Interpersonal skills, Delibrating and Questioning skills) scale. From the Table 8, it is evident that there is a acceptable reliability with coefficient alphas ranging from 0.913 to 0.525. Table 11: Ranking for Skepticism dimension - Self determing Self determing I often accept other peoples’ explanations without further thought. I tend to immediately accept what other people tell me. It is easy for other people to convince me. I usually accept things I see, read or hear at face value. Most often I agree with what the others in my group think. Mean S.D Ranking 1.5 5.07 0.78 5.07 4.64 4.60 4.29 1.22 1.5 0.88 3 1.15 4 1.07 5 Table 11 shows the descriptive statistics along with ranking of each item of self determing. The ranking is based on the mean scores. From the analysis, majority of the respondents were agreed (Mean > 4) the following items namely, I often accept other peoples’ explanations without further thought, I tend to immediately accept what other people tell me, It is easy for other people to convince me, I usually accept things I see, read or hear at face value and Most often I agree with what the others in my group think. The item ‘ I often accept other peoples’ explanations without further thought and I tend to immediately accept what other people tell me’ had the frst rank and ‘Most often I agree with what the others in my group think’ had the last rank. 24 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Table 12: Ranking for Skepticism dimension - Curiosity Curiosity Discovering new information is fun I like searching for knowledge I think that learning is exciting The prospect of learning excites me I relish learning Mean S.D 5.07 Ranking 0.81 1 4.98 4.86 0.75 2 0.93 3 4 4.79 1.00 4.64 0.91 5 Table 12 shows the descriptive statistics along with ranking of each item of curiosity. The ranking is based on the mean scores. From the analysis, majority of the respondents were agreed (Mean > 5) the following items namely, Discovering new information is fun, I like searching for knowledge, I think that learning is exciting, The prospect of learning excites me and I relish learning. The item ‘ Discovering new information is fun’had the frst rank and ‘I relish learning’ had the last rank. Table 13: Ranking for Skepticism dimension – Self confidence Self confidence I am confident of my abilities I have confidence in myself 4.95 I don’t feel sure of myself I feel good about myself I am self-assured. Mean S.D 5.02 Ranking 0.60 1 0.80 2 1.09 3 1.01 4 1.09 5 4.88 4.76 4.45 Table 13 shows the descriptive statistics along with ranking of each item of self confidence. The ranking is based on the mean scores. From the analysis, majority of the respondents were agreed (Mean > 5) the following items namely, I am confident of my abilities, I have confidence in myself, I don’t feel sure of myself, I feel good about myself and I am self- assured.. The item ‘ I am confident of my abilities’had the frst rank and ‘I am self-assured’ had the last rank. 25 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Table 14: Ranking for Skepticism dimension – Interpersonal skills Inter personal skills I am interested in what causes people to behave the way that they do I like to understand the reason for other peoples’ behavior The actions people take and the reasons for those actions are fascinating Other peoples’ behavior doesn’t interest me I seldom consider why people behave in a certain way Mean S.D Ranking 1 4.81 0.83 4.76 0.82 2 3 4.62 0.83 4.52 4.40 1.25 4 1.21 5 Table 14 shows the descriptive statistics along with ranking of each item of Inter personal skills. The ranking is based on the mean scores. From the analysis, majority of the respondents were agreed (Mean > 4) the following items namely, I am interested in what causes people to behave the way that they do, I like to understand the reason for other peoples’ behavior , The actions people take and the reasons for those actions are fascinating, Other peoples’ behavior doesn’t interest me and I seldom consider why people behave in a certain way. The item ‘ I am interested in what causes people to behave the way that they do’had the frst rank and ‘I seldom consider why people behave in a certain way’ had the last rank. Table 15: Ranking for Skepticism dimension – Deliberating Deliberating I wait to decide on issues until I can get more information I like to ensure that I’ve considered most available information before making a decision I take my time when making decisions I don’t like to decide until I’ve looked at all of the readily available information. I dislike having to make decisions quickly Mean S.D 5.21 Ranking 0.57 1 2 5.17 0.76 4.98 0.84 3 4 4.79 0.95 4.33 1.32 5 Table 15 shows the descriptive statistics along with ranking of each item of Delibrating. The ranking is based on the mean scores. From the analysis, majority of the respondents were agreed (Mean > 4) the following items namely, I wait to decide on issues until I can get more information, I like to ensure that I’ve considered most available information before making a decision, I take my time when making decisions, I don’t like to decide until I’ve looked at all of the readily available information and I dislike having to make decisions quickly. The item ‘I wait to decide on issues until I can get more information’had the frst rank and ‘I dislike having to make decisions quickly’ had the last rank. 26 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

` Statisticalpeerreview Table 16: Ranking for Skepticism dimension – Questioning skills Questioning skills I frequently question things that I see or hear I enjoy trying to determine if what I read or hear is true My friends tell me that I usually question things that I see or hear I often reject statements unless I have proof that they are true I usually notice inconsistencies in explanations Mean S.D 4.88 4.79 Ranking 0.71 1 0.81 2 3 4.52 0.86 4 4.48 1.11 4.26 1.36 5 Table 16 shows the descriptive statistics along with ranking of each item of Questioning skills. The ranking is based on the mean scores. From the analysis, majority of the respondents were agreed (Mean > 4) the following items namely, I frequently question things that I see or hear, I enjoy trying to determine if what I read or hear is true, My friends tell me that I usually question things that I see or hear, I often reject statements unless I have proof that they are true and I usually notice inconsistencies in explanations. The item ‘ I frequently question things that I see or hear’had the frst rank and ‘I usually notice inconsistencies in explanations’ had the last rank. Independent sample t-test Independent sample t test is used to find out whether the mean of two unrelated groups (independent variable) are equal or not based on the same dependent variable. The data should be in the following format (Kent University, 2015; Laerd Statistics, 2015a). ?Independent variable must be in categorical data ?Dependent variable should be measured on a continuous scale (interval or ratio) ?The data should contain without outliers. Outlier means a value(s) which is deviate from the whole data. ?The data should follow approximately normally distributed for each of the group of independent variable. ?The variability within the independent variable is not distinct. ?F-value and p-value for Levene’s test are used to test the homogeneity of variances within two group of independent variable. Here p-value must be greater than 0.05, then we conclude that the two groups’ variance are same. 27 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

` Statisticalpeerreview ?Descriptive statistic (Mean, SD and SE) for two groups based on the dependent variable. ?t-value and p-value for t test are used for compare the mean of two groups based on dependent variable. Table 17: Mean difference in skepticism dimensions between gender Gender (n=42) Male (n=26) Mean±SD 2.35±0.55 2.13±0.79 4.90±0.83 4.81±0.65 4.35±0.48 4.13±0.44 3.88±0.39 3.80±0.40 4.88±0.59 4.93±0.52 4.64±0.60 4.50±0.58 Skepticism dimensions Female (n=16) t-value p-value Self determing Curiosity Self confidence Interpersonal skills Delibrating Questioning skills 1.106 0.359 1.502 0.673 -0.268 0.739 0.276 0.722 0.141 0.505 0.790 0.464 An independent sample t test was performed comparing the mean ‘Skepticism dimensions’ between Male and Female . Table 15 results indicated that all the dimensions of ‘Skepticism’ namely Self determing (Male: M = 2.35, SD =0.55, Vs Female M= 2.13, SD=0.79, t= 1.106, p=0.276>0.05), Curiosity (Male: M = 4.90, SD =0.83, Vs Female M= 4.81, SD=0.65, t= 0.359, p=0.722>0.05), Self-confidence (Male: M = 4.35, SD =0.48, Vs Female M= 4.13, SD=0.44, t= 1.502, p=0.141>0.05), Interpersonal skills (Male: M = 3.88, SD =0.39, Vs Female M= 3.80, SD=0.40, t= 0.673, p=0.505>0.05), Delibrating (Male: M = 4.88, SD =0.59, Vs Female M= 4.93, SD=0.52, t= -0.268, p=0.790>0.05), and Questioning skills (Male: M = 4.64, SD = 0.60, Vs Female M= 4.50, SD=0.58, t= 0.739, p=0.464>0.05) were not significant in both the male and female. Analysis of Variance (ANOVA) One way – ANOVA is one of the mean comparison test. This test is used to ascertain whether the mean of more than two groups (independent variable) are equal or not based on the dependent variable. The data should satisfy the following conditions (Laerd Statistics, 2015b; School of Public Health, 2015): ?Independent variable must be in categorical data 28 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

` Statisticalpeerreview ?Dependent variable should be measured on a continuous scale (interval or ratio) ?The data should contain without outliers. Outlier means a value(s) which is deviate from the whole data. ?The data should follow approximately normally distributed for each of the group of independent variable. ?The variability within the independent variable is not distinct. ?Descriptive statistic (Mean, SD and SE) for groups based on the dependent variable. ?F-value and p-value are used to compare the mean values between the groups of independent variable. ?Multiple comparison tests give the information about whether combinations of two groups’ means are equal. Table 18: Mean difference in skepticism dimensions between experience Experience in years (n=42) <=2.5 (n=11) Mean±SD 2.44±0.54 2.30±0.68 2.13±0.80 2.16±0.64 0.453 5.16±0.56 5.35±0.59 4.51±0.56 4.28±0.81 6.915 4.31±0.56 4.35±0.40 4.16±0.49 4.20±0.47 0.370 3.85±0.48 4.02±0.28 3.71±0.25 3.78±0.48 1.221 5.00±0.53 4.97±0.64 5.00±0.26 4.60±0.65 1.251 4.55±0.71 4.55±0.45 4.67±0.66 4.60±0.60 0.085 Skepticism dimensions 5.1-17.0 (n=9) >=17.1 (n=10) 2.6-5.0 (n=12) F-value p-value Self determing Curiosity Self confidence Interpersonal skills Delibrating Questioning skills **p<0.01 0.717 0.001** 0.775 0.315 0.305 0.968 The obtained F-value and p-value for Curiosity are 6.915 and 0.001 respectively. Here p- value is less than 0.05, it leads to reject the null hypothesis and support the alternative hypothesis. Hence, there is a statistically significant difference between years of experience. In which Curiosity has a higher mean of 5.35 in 2.6-5.0 years compared to other years of experience. The p-value is greater than 0.05 for self determing, Self-confidence, Interpersonal skills, Delibrating and Questioning skills. Hence there is no significant difference in mean self 29 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

` Statisticalpeerreview determing, Self-confidence, Interpersonal skills, Delibrating and Questioning skills between years of experience. Table 19: Mean difference in skepticism dimensions between level of education Highest level of education (n=42) Bachelors (n=10) (n=14) Mean±SD 2.46±0.63 2.47±0.70 2.00±0.57 2.865 4.86±0.83 5.29±0.62 4.54±0.69 4.367 4.04±0.53 4.31±0.48 4.34±0.41 1.512 3.80±0.33 3.94±0.40 3.81±0.43 0.547 4.82±0.70 4.96±0.54 4.89±0.52 0.170 4.42±0.49 4.34±0.61 4.87±0.52 4.242 Skepticism dimensions Others (n=18) Masters F-value p-value Self determing Curiosity Self confidence Interpersonal skills Delibrating Questioning skills *p<0.05 0.069 0.019* 0.233 0.583 0.844 0.022* The obtained F-value and p-value for Curiosity are 4.367 and 0.019 and Questioning skills with F-value 4.242 and p-value 0.022 respectively. Here p-value is less than 0.05, it leads to reject the null hypothesis and support the alternative hypothesis. Hence, there is a statistically significant difference between levels of education. In which Curiosity has a higher mean of 5.29 in masters compared to other level of education. In Questioning skills rest of education has higher mean of 4.87 compared to Bachelors and Masters. The p-value is greater than 0.05 for self determing, Self-confidence, Interpersonal skills and Delibrating. Hence there is no significant difference in mean self determing, Self- confidence, Interpersonal skills and Delibrating between levels of education. 30 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

` Statisticalpeerreview Table 20: Mean difference in skepticism dimensions between professional position Professional position (n=42) Staff (n=7) (n=9) Mean±SD Skepticism dimensions F- value p- value Supervisor (n=3) Manager (n=9) Partner (n=8) Others (n=6) Senior Self determing 2.23±0.47 2.04±0.82 2.80±0.35 Curiosity 4.91±0.46 5.02±0.74 5.20±0.35 Self confidence 4.14±0.61 4.42±0.29 4.53±0.23 Interpersonal skills Delibrating 5.03±0.60 4.80±0.56 5.33±0.31 Questioning skills 2.36±0.84 2.38±0.56 2.10±0.47 0.745 0.595 4.67±0.95 4.60±0.89 5.07±0.81 0.570 0.722 4.16±0.64 4.23±0.33 4.23±0.53 0.573 0.720 3.77±0.39 3.89±0.48 3.93±0.23 3.98±0.42 3.63±0.38 3.97±0.27 0.912 0.484 5.00±0.35 4.70±0.76 4.77±0.59 0.802 0.556 4.60±0.75 4.49±0.50 4.20±0.53 4.87±0.66 4.43±0.57 4.70±0.43 0.874 0.508 The p-value is greater than 0.05 for self determing, Curiosity, Self-confidence, Interpersonal skills, Delibrating and Questioning skills. Hence there is no significant difference in mean self determing, Curiosity, Self-confidence, Interpersonal skills Delibrating and Questioning skills between different Professional positions. Chi-square tests The association between two categorical variables is tested through Chi-square test. The data should follow two conditions. (i) The two variables should be in ordinal or nominal scale (i.e) categorical. (ii) The two variables consist of two or more independent groups. Chi-square value and p-value give the information about whether there is an association between two categorical variables. Phi-value and Cramer’s V are used to ascertain the strength of association between variables (Whether good association or bad association). 31 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

` Statisticalpeerreview Table 21: Association between level of skepticism and gender Gender (n=42) Male (n=26 ) n(%) 12(46.2) 14(53.8) 26(100.0) Level of Skepticism Female (n=16) Total Low skepticism High skepticism Total Chi-square value: 0.059; p-value: 0.808>0.05 8(50.0) 8(50.0) 16(100.0) 20(47.6) 22(52.4) 42(100.0) From Table 21 the obtained chi-square value and p- values are 0.059 and 0.808 respectively. Here, the p-value is greater than 0.05, and then we accept the null hypothesis H0 and support the alternative hypothesis H1. It concludes that there is no statistically significant association exists between level of Skepticism and Gender. Table 22: Association between level of skepticism and experience Experience in years (n=42) <=2.5 (n=11) n(%) 2.6-5.0 (n=12) 5.1-17.0 (n=9) >=17.1 (n=10) Level of Skepticism Total Low skepticism High skepticism Total Phi-value: 0.300 p-value: 0.287>0.05 4 (36.4) 7 (63.6) 11 (100.0) 4 (33.3) 8 (66.7) 12 (100.0) 5 (55.6) 4 (44.4) 9 (100.0) 7 (70.0) 3 (30.0) 10 (100.0) 20 (47.6) 22 (52.4) 42 (100.0) From Table 22 the obtained Phi-value and p- values are 0.300 and 0.287 respectively. Here, the p-value is greater than 0.05, and then we accept the null hypothesis H0 and support the alternative hypothesis H1. It concludes that there is no statistically significant association exists between level of Skepticism and years of experience. 32 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

` Statisticalpeerreview Table 23: Association between level of skepticism and level of education Highest level of education (n=42) Bachelors (n=10) n(%) 5 (50.0) 5 (50.0) 10 (100.0) Level of Skepticism Masters (n=14) Others (n=18) Total Low skepticism High skepticism Total Fisher exact value: 0.074; p-value: 0.938>0.05 7 (50.0) 7 (50.0) 14 (100.0) 8 (44.4) 10 (55.6) 18 (100.0) 20 (47.6) 22 (52.4) 42 (100.0) From Table 23 the obtained fisher exact value and p- values are 0.074 and 0.938 respectively. Here, the p-value is greater than 0.05, and then we accept the null hypothesis H0 and support the alternative hypothesis H1. It concludes that there is no statistically significant association exists between level of Skepticism and level of education. Table 24: Association between level of skepticism and professional position Professional position (n=42) Staff (n=7) (n=9) n(%) 3 (42.96) 4 (44.4) 1 (33.3) 5 (55.6) 2 (66.7) 7 (100.0) 9 (100.0) 3 (100.0) Level Skepticism of Senior Supervisor (n=3) Manager (n=9) Partner (n=8) Others (n=6) Total Low skepticism High skepticism 4 (57.1) Total Phi-value: 0.120; p-value: 0.988>0.05 5 (55.6) 4 (44.4) 9 (100.0) 8 (100.0) 6 (100.0) 42(100.0) 4 (50.0) 3 (50.0) 20 (47.6) 4 (50.0) 3 (50.0) 22(52.4) From Table 24 the obtained Phi-value and p- values are 0.120 and 0.988 respectively. Here, the p-value is greater than 0.05, and then we accept the null hypothesis H0 and support the alternative hypothesis H1. It concludes that there is no statistically significant association exists between level of Skepticism and professional position. Correlation The strength and direction of association between two variables are measured by Pearson correlation coefficient. The two variables must be measured on a continuous (interval) scale. The correlation coefficient (r) ranges from -1 to 1. Based on the sign of the correlation coefficient, it can be concluded as follows. 33 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

` Statisticalpeerreview ?If rX,Y is positive – The two variables X and Y are in positive relationship. ?If rX,Y is negative – The two variables are in negative relationship. ?If rX,Y = 0, There is no relationship between X & Y ?Significance (p) value is used to whether the two variables are in relationship or not. ?Correlation coefficient (r) value is used to find out whether the two variables are positively relationship or negative relationship. Table 25: Correlation between skepticism dimensions Skepticism dimensions Self determing Curiosity Self confidence Interpersonal skills Delibrating Questioning skills **p<0.01, *p<0.05 Self determing Curiosity Self Interpersonal skills Delibrating Questioning confidence skills 1 -0.003 -0.055 -0.086 -0.114 -0.423** 1 0.174 0.044 0.364* 0.341* 1 0.257 0.133 0.463** 1 0.243 0.338* 1 0.135 1 Table 25 present the Pearson correlation between Skepticism dimension variables respectively. The correlation values in the table are significant at the 1% and 5% level. There is significant negative correlation between self determing and Questioning skills (r=-0.423, p<0.01). The negative correlation indicates that the self determing increase the Questioning skill decreases. There is a significant positive correlation between Curiosity and Interpersonal skills (r=0.364, p<0.05), Curiosity and Delibrating (r=0.341, p<0.01). The positive correlation indicates that Curiosity increases Interpersonal skills and Delibrating also increases. There is a significant positive correlation between Questioning skills and Self-confidence (r=0.463, p<0.01), Questioning skills and Interpersonal skills (r=0.338, p<0.05). The positive correlation indicates that Questioning skills increases Self-confidence and Interpersonal skills also increases. The bolded value presents in Table 23 are either positive or negative significant correlation. 34 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

` Statisticalpeerreview Figure 6: Scatter diagram for skepticism dimensions Information Table 26: Descriptive statistics for financial ratios in High and Low risk information High risk information Low risk information 2012 2011 2010 Mean 1.90 1.39 1.20 0.68 0.53 0.50 Debt equity ratio 0.29 0.38 Financial ratios 2012 2011 Mean 1.54 0.56 0.35 2010 Current ratio Net margin ratio 1.40 0.53 0.38 1.27 0.50 0.43 0.43 Table 26 presents the descriptive statistics for financial information from 2010 to 2012 for high risk information. The mean current ratio is higher in 2012 (1.90) compared to 2010 and 2011. The mean net margin is higher in 2012 (0.68) compared to 2010 and 2011. The mean debt equity ratio is higher in 2010 (0.43) compared to 2011 and 2012. 35 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Statisticalpeerreview Similarly for low risk information the mean current ratio is higher in 2012 (1.54) compared to 2010 and 2011. The mean net margin is higher in 2012 (0.56) compared to 2010 and 2011. The mean debt equity ratio is higher in 2010 (0.43) compared to 2011 and 2012. Table 27: Descriptive statistics for perception in High and Low risk information Low risk perception High risk perception Mean S.D Ranking Mean S.D Ranking Perception Personal financial obligations by ZZZs’ key personnel Domination of management by a single person or small group without compensation controls Inadequate monitoring controls, including automated controls and controls over interim financial reporting Adverse relationship between company and employees 7.90 1.82 1 4.19 2.47 2 7.69 1.65 2 5.19 2.81 1 7.45 1.71 3 3.86 2.31 5 6.76 2.25 4 3.98 2.46 3 Changes in compensation and Promotions, compensation or other rewards inconsistent with expectations Ineffective communications, implementation, support or enforcement of ethical climate 6.74 1.42 5 3.90 2.37 4 Table 27 shows the descriptive statistics along with ranking of each item of Perception. The ranking is based on the mean scores. From the analysis, majority of the respondents were agreed (Mean > 7) in high risk perception the following items namely, Personal financial obligations by ZZZs’ key personnel, Domination of management by a single person or small group without compensation controls, Inadequate monitoring controls, including automated controls and controls over interim financial reporting, Adverse relationship between company and employees and Ineffective communications, implementation, support or enforcement of ethical climate. The item ‘ Personal financial obligations by ZZZs’ key personnel’ had the first rank and ‘Ineffective communications, implementation, support or enforcement of ethical climate’ had the last rank. Similarly majority of the respondents were agreed (Mean > 4) in low risk perception the following items namely, Domination of management by a single person or small group without 36 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Phd Assistance™ - Your trusted mentor since 2001 I www.phdassisatnce.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@Phdassistance.com Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent

Statisticalpeerreview ` Statisticalpeerreview compensation controls, Personal financial obligations by ZZZs’ key personnel, Adverse relationship between company and employees, Ineffective communications, implementation, support or enforcement of ethical climate and Inadequate monitoring controls, including automated controls and controls over interim financial reporting. The item ‘Domination of management by a single person or small group without compensation controls’ had the first rank and ‘Inadequate monitoring controls, including automated controls and controls over interim financial reporting’ had the last rank. Table 28: Descriptive statistics for judgment in High and Low risk information High risk Judgment Low risk Judgment Judgment Mean S.D Ranking Mean S.D Ranking Aggressive or unrealistic forecasts management in maintaining ZZZ's earnings trend. Warranties expense in 2012 is £102,846, 6% increase from the previous year by 7.36 1.87 1 3.98 2.05 1 Recurring management attempts to justify marginal or inappropriate accounting based on materiality 7.14 1.62 2 2.95 1.70 4 Rapid especially compared to that of the prior years. See ratios analysis table growth or unusual profitability 6.55 1.95 3 3.31 1.79 3 Complex or unstable organizational structure 5.40 2.14 4 3.55 2.40 2 Table 28 shows the descriptive statistics along with ranking of each item of Judgment. The ranking is based on the mean scores. From the analysis, majority of the respondents were agreed (Mean > 5) in high risk judgment the following items namely, Aggressive or unrealistic forecasts by management in maintaining ZZZ's earnings trend. Warranties expense in 2012 is £102,846, 6% increase from the previous year, Recurring management attempts to justify marginal or inappropriate accounting based on materiality, Rapid growth or unusual profitability especially compared to that of the prior years and Complex or unstable organizational structure. The item ‘Aggressive or unrealistic forecasts by management in maintaining ZZZ's earnings 37 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Phd Assistance™ - Your trusted mentor since 2001 I www.phdassisatnce.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@Phdassistance.com Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent

Statisticalpeerreview ` Statisticalpeerreview trend. Warranties expense in 2012 is £102,846, 6% increase from the previous year’ had the first rank and ‘Complex or unstable organizational structure’ had the last rank. Similarly majority of the respondents were agreed (Mean > 3) in low risk judgment the following items namely, Aggressive or unrealistic forecasts by management in maintaining ZZZ's earnings trend. Warranties expense in 2012 is £102,846, 6% increase from the previous year, Complex or unstable organizational structure, Rapid growth or unusual profitability especially compared to that of the prior years. See ratios analysis table and Recurring management attempts to justify marginal or inappropriate accounting based on materiality. The item ‘Aggressive or unrealistic forecasts by management in maintaining ZZZ's earnings trend. Warranties expense in 2012 is £102,846, 6% increase from the previous year’ had the first rank and ‘Recurring management attempts to justify marginal or inappropriate accounting based on materiality’ had the last rank. Table 29: Descriptive statistics for decision in High and Low risk information Low risk Decision High risk Decision Mean S.D Decision Ranking Mean S.D Ranking What is the risk of financial statement fraud attributable to the incentives faced by ZZZs' management What is the risk of financial statement fraud attributable to the opportunities available to ZZZs 7.88 1.47 1 3.45 2.14 3 7.38 1.91 2.5 3.88 2.07 1 Based on all the information you have reviewed in this case, what is the overall risk of material financial statement fraud for ZZZs 7.38 1.55 2.5 3.52 2.00 2 What is the risk of financial statement fraud attributable to ZZZs management’s attitude or character 7.31 1.60 4 3.29 1.74 4 Table 29 shows the descriptive statistics along with ranking of each item of Decision. The ranking is based on the mean scores. From the analysis, majority of the respondents were high (Mean > 7) in high risk decision the following items namely, What is the risk of financial statement fraud attributable to the incentives faced by ZZZs' management, What is the risk of financial statement fraud attributable to the opportunities available to ZZZs, Based on all the 38 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Phd Assistance™ - Your trusted mentor since 2001 I www.phdassisatnce.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@Phdassistance.com Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent

Statisticalpeerreview ` information you have reviewed in this case, what is the overall risk of material financial statement fraud for ZZZs and What is the risk of financial statement fraud attributable to ZZZs management’s attitude or character. The item ‘ What is the risk of financial statement fraud attributable to the incentives faced by ZZZs' management’had the frst rank and ‘What is the risk of financial statement fraud attributable to ZZZs management’s attitude or character’ had the last rank. Similarly majority of the respondents were low (Mean > 2) in low risk decision the following items namely, What is the risk of financial statement fraud attributable to the opportunities available to ZZZs, Based on all the information you have reviewed in this case, what is the overall risk of material financial statement fraud for ZZZs, What is the risk of financial statement fraud attributable to the incentives faced by ZZZs' management and What is the risk of financial statement fraud attributable to ZZZs management’s attitude or character. The item ‘What is the risk of financial statement fraud attributable to the opportunities available to ZZZs’had the frst rank and ‘What is the risk of financial statement fraud attributable to ZZZs management’s attitude or character’ had the last rank. Table 30: Reliability analysis for fraud risk (Low and High) factors in High and low risk High risk Number of items 5 Low risk Number of items 5 Fraud risk factors Range (Max- Min) 5.40 (9.40- 4.00) 6.25 (8.75- 2.50) 6.25 (9.00- 2.75) Range (Max- Min) Cronbach’s alpha Cronbach’s alpha Mean S.D Mean S.D 4.22 1.97 7.20 0.852 Perception 7.31 1.10 0.589 (8.40- 1.20) 4 4 3.45 1.71 6.50 0.875 Judgment 6.61 1.31 0.629 (7.75- 1.25) 4 4 3.54 1.74 5.50 0.895 Decision 7.49 1.21 0.724 (7.00- 1.50) S.D- Standard Deviation; Max- Maximum, Min-Minimum Table 30 presents the descriptive statistics for each fraud risk factors and the reliability analysis outcome using the Cronbach’s alpha method in order to measure the reliability of each multi-item of fraud risk factors (i.e. Perception, Judgment and Decision) scale. From the Table 39 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` 30, it is evident that there is an acceptable reliability with coefficient alphas ranging from 0.72 to 0.589 in high risk and coefficient alphas ranging from 0.895 to 0.852 in low risk respectively. Independent sample t-test Table 31: Mean difference in fraud risk (High and low) factors between gender Gender (n=42) Fraud risk factors Male Female t-value p-value (n=26) (n=16) Mean±SD High risk Perception 7.40±1.09 7.16±1.14 0.674 0.504 Judgment 6.71±1.22 6.45±1.47 0.616 0.541 Decision 7.63±1.02 7.27±1.48 0.931 0.358 Low risk Perception 4.39±2.08 3.95±1.81 0.701 0.487 Judgment 3.73±1.88 2.98±1.32 1.391 0.172 Decision 3.99±1.89 2.80±1.17 2.263 0.029* *p<0.05 The obtained t-value and p-value for Decision in low risk are 2.263 and 0.029 respectively. Here p-value is less than 0.05, it leads to reject the null hypothesis and support the alternative hypothesis. Hence, there is a statistically significant difference between male and female. In which Decision has a higher mean of 3.99 in male compared to female. The p-value is greater than 0.05 for Perception, Judgment and Decision in high risk and Perception and Judgment in low risk. Hence there is no significant difference in mean Perception, Judgment and Decision in high risk and Perception and Judgment in low risk between male and female. 40 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview Analysis of Variance (ANOVA) Table 32: Mean difference in fraud risk (High and low) factors between experience Experience in years (n=42) <=2.5 (n=11) Mean±SD Fraud risk factors 5.1-17.0 (n=9) >=17.1 (n=10) 2.6-5.0 (n=12) F-value p-value High risk Perception 6.64±1.15 7.17±0.78 7.64±1.41 7.92±0.65 3.177 Judgment 6.68±1.62 6.15±0.93 6.81±1.58 6.93±1.08 0.759 Decision 7.09±1.73 7.27±0.83 7.61±1.34 8.08±0.54 1.368 Low risk Perception 4.56±1.63 5.22±2.00 3.18±1.99 3.60±1.84 2.562 Judgment 4.18±1.95 4.27±1.64 2.33±1.10 2.65±1.09 4.550 Decision 3.64±1.77 4.58±1.76 2.58±1.32 3.03±1.53 3.039 **p<0.01, *p<0.05 0.035* 0.524 0.267 0.069 0.008** 0.041* The obtained F-value and p-value for Perception are 3.177 and 0.035. Here p-value is less than 0.05, it leads to reject the null hypothesis and support the alternative hypothesis. Hence, there is a statistically significant difference between years of experience. In which Perception has a higher mean of 7.92 in >=17.1 years of experience compared to other years of experience. The obtained F-value and p-value for Judgment are 4.550 and 0.008 and Decision with F- value 3.039and p-value 0.041respectively. Here p-value is less than 0.05, it leads to reject the null hypothesis and support the alternative hypothesis. Hence, there is a statistically significant difference between years of experience. In which Judgment has a higher mean of 4.27 in 2.6-5.0 years of experience compared to other years of experience. In Decision 2.6-5.0 years of experience has higher mean 4.58 compared to other years of experience. The p-value is greater than 0.05 for Judgment and Decision in high risk and Perception in low risk. Hence there is no significant difference in mean Judgment and Decision in high risk and Perception in low risk between years of experience. 41 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Table 33: Mean difference in fraud risk (High and low) factors between level of education Highest level of education (n=42) Bachelors (n=10) (n=14) Mean±SD Others (n=18) Fraud risk factors Masters F-value p-value High risk Perception Judgment Decision Low risk Perception Judgment Decision 7.38±0.89 7.17±1.02 7.38±1.30 0.158 6.60±1.40 6.48±1.53 6.72±1.13 0.127 7.25±0.90 7.34±1.47 7.74±1.17 0.663 0.854 0.881 0.521 4.16±1.43 4.89±2.17 3.74±2.02 1.347 3.63±2.13 3.64±1.55 3.19±1.64 0.332 3.93±1.81 3.84±1.74 3.08±1.70 1.074 0.272 0.719 0.352 The p-value is greater than 0.05 for Perception, Judgment and Decision in high risk and Perception, Judgment and Decision in low risk. Hence there is no significant difference in mean Perception, Judgment and Decision in high risk and Perception, Judgment and Decision in low risk between levels of education. Table 34: Mean difference in fraud risk (High and low) factors between professional position Professional position (n=42) Staff (n=7) (n=9) Mean±SD Fraud risk factors F- value p- value Supervisor (n=3) Manager (n=9) Partner (n=8) Others (n=6) Senior High risk Perception 6.94±1.43 7.27±1.04 8.53±0.81 Judgment 7.18±0.86 6.61±1.32 7.25±1.09 Decision 7.39±1.14 7.69±0.56 8.42±0.52 Low risk Perception 4.69±1.90 3.73±2.20 6.87±1.72 Judgment 4.50±2.23 2.69±0.99 4.42±2.18 Decision 3.64±1.99 2.78±1.30 4.58±2.24 7.07±1.35 7.48±0.74 7.33±0.77 1.027 0.416 5.67±1.93 6.97±0.80 6.58±0.77 1.560 0.196 6.64±1.92 7.91±0.40 7.54±1.26 1.594 0.187 3.22±1.52 4.55±1.98 4.17±1.59 1.988 0.104 2.58±1.48 3.69±1.59 3.83±1.64 1.785 0.141 2.86±1.56 4.31±1.68 4.00±1.94 1.280 0.294 The p-value is greater than 0.05 for Perception, Judgment and Decision in high risk and Perception, Judgment and Decision in low risk. Hence there is no significant difference in mean 42 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Perception, Judgment and Decision in high risk and Perception, Judgment and Decision in low risk between professional positions. Correlation Table 35: Correlation between fraud risk factors Perception -High risk Judgment Decision Perception- Judgment Decision Low risk High risk Perception 1 Judgment Decision Low risk Perception -.149 Judgment Decision **p<0.01 .522** 1 .706** .761** 1 -.149 -.017 -.079 -.098 .103 .034 .087 .088 .072 .698** 1 .774** .780** 1 -.017 .103 .088 -.079 .034 .072 1 -.098 .087 Table 35 present the Pearson correlation between fraud risk variables respectively. The correlation values in the table are significant at the 1% and 5% level. There is significant positive correlation in high risk between Perception and Judgment (r=0.522, p<0.01), Perception and Decision (r=0.706, p<0.01) and Judgment and Decision (r=0.761, p<0.01). The positive correlation indicates that the Perception increases the Judgment and Decision also increases. There is a significant positive correlation in low risk between Perception and Judgment (r=0.698, p<0.01), Perception and Decision (r=0.774, p<0.01) and Judgment and Decision (r=0.780, p<0.01). The positive correlation indicates that the Perception increases the Judgment and Decision also increases. The bolded value presents in Table 33 are positive significant correlation. 43 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Figure 7: Scatter diagram for high risk perception, judgment and decision Figure 8: Scatter diagram for low risk perception, judgment and decision 44 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Model 1: H1a: Table 36: Reliability and validity estimates for information, perception, judgment and Decision Composite Reliability (CR > 0.7) Average Variance Extracted (AVE > 0.5) Factors R-square Leverage 0.427 Liquidity 1.000 1.000 0.522 Profitability 1.000 1.000 0.490 Perception 0.920 0.697 Judgment 0.921 0.746 0.727 Decision 0.958 0.851 0.877 Table 1 presents the reliability and validity estimates for information, perception, judgment and decision. From the above table all the factors satisfies the criteria for composite reliability 45 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` (C.R>0.7). All measures have a loading level above 0.70. In addition, measurement residuals are small. All loadings have the expected signs (i.e., non-negative) and are significant at the 0.001 level (one-tailed). Further, all constructs present a composite reliability (see, Fornell and Larcker 1981) above 0.70, the benchmark level suggested by Nunnally (1978) and Average Variance Extracted (AVE>0.5). In all our models, average variance extracted (AVE) ranges between 0.70 and 1.00, indicating satisfactory convergent validity for the constructs. Table 37: Discriminate validity Decision Judgment Perception Leverage Liquidity Profitability 0.9202 Decision 0.903 0.863 Judgment 0.884 0.824 0.835 Perception -0.754 -0.696 -0.653 Leverage 0.804 0.732 0.723 -0.875 1.000 Liquidity 0.787 0.715 0.700 -0.851 0.993 1.000 Profitability Table 38: Pathways coefficients for Information, Perception, Judgment and Decision Information, Perception, Judgment Pathways (regression weights) p-values and Decision Judgment?Decision 0.545 0.000** Perception? Decision 0.434 0.000** Perception? Judgment 0.613 0.000** Leverage? Judgment -0.191 0.180 Liquidity? Judgment 0.005 0.993 Proftability? Judgment 0.118 0.824 46 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` Perception?Leverage -0.653 0.000** Perception?Liquidity 0.723 0.000** Perception?Profitability 0.700 0.000** **p<0.01 The PLS path coefficients for information, perception , judgment and decision shown in Table 3. Overall, our results suggest that judgment (β=0.545, p<0.01) and perception (β=0.434, p<0.01) have positive significant effect on Decision. Likewise perception have positive significant effect (β=0.613, p<0.01) on judgment and While perception have positive significant effect on two financial indicators liquidity and profitability and perception has negative significant effect on leverage. Thus model is supported. H1 and H2a should be tested by using the full model above and by getting the pathways in the table above H2b: There is a significant relationship between components assessment and overall assessment. Table 39: Correlation between high risk incentive, opportunity, attitude and overall risk decision Overall risk decision .579** .503** .444** 1 High risk Incentive Opportunity Attitude .452** .351* 1 Incentive Opportunity Attitude Overall risk decision **p<0.01, *p<0.05 1 .129 1 Table 57 present the Pearson correlation between incentive, opportunity, attitude and overall risk decision for high risk respectively. The correlation values in the table are significant at the 1% and 5% level. There is significant positive correlation in high risk between incentive and attitude (r=0.452, p<0.01), incentive and overall risk decision (r=0.579, p<0.01). The 47 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` positive correlation indicates that the incentive increases the attitude and overall risk decision also increases. There is significant positive correlation between opportunity and attitude (r=0.351, p<0.01), opportunity and overall risk decision (r=0.503, p<0.01). The positive correlation indicates that the opportunity increases the attitude and overall risk decision also increases. There is significant positive correlation between attitude and overall risk decision (r=0.444, p<0.01). The bolded value presents in Table 55 are positive significant correlation. Table 40: Correlation between low risk incentive, opportunity, attitude and overall risk decision Overall risk decision .756** .696** .836** 1 Low risk Incentive Opportunity Attitude .566** 1 .683** .597** 1 Incentive Opportunity Attitude Overall risk decision **p<0.01 1 Table 58 present the Pearson correlation between incentive, opportunity, attitude and overall risk decision for low risk respectively. The correlation values in the table are significant at the 1% and 5% level. There is significant positive correlation in low risk between incentive and opportunity (r=0.566, p<0.01), incentive and attitude (r=0.683, p<0.01), incentive and overall risk decision (r=0.756, p<0.01). The positive correlation indicates that the incentive increases the opportunity, attitude and overall risk decision also increases. There is significant positive correlation between opportunity and attitude (r=0.597, p<0.01), opportunity and overall risk decision (r=0.696, p<0.01). The positive correlation indicates that the opportunity increases the attitude and overall risk decision also increases. There is significant positive correlation between attitude and overall risk decision (r=0.836, p<0.01). The bolded value presents in Table 56 are positive significant correlation. Regression Multiple regression analysis is similar to the linear regression analysis. In the linear regression, we have to use only one independent variable and dependent variable. But in the multiple regressions, we can to use more than one independent variable and one dependent 48 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Statisticalpeerreview ` variable. Both regression analyses are used to predict the value of a dependent variable based on the value of independent variable. Dependent variable means the variable we want to predict and independent variable means the variable we are using to predict the value of the dependent variable. ?R square (R2) value explains what percent of variance in the dependent variable that can be explained by the independent variable. ?F-ratio in the ANOVA table tells whether the overall regression model is a good fit or not for the data. ?Estimated model coefficients table contains the following estimators: Through t-value and p-value for each independent variable, we can know whether each independent variable is signifcantly predicting the dependent variable. Beta (β) coefcients are the point estimator of independent variables. This table also contains the interval estimator of independent variable (Syke, 1993). Table 41: Association between high risk incentive, opportunity and attitude on overall risk decision Unstandardized Coefficients Independent variables R Square F-change t-value p-value Beta S.E (Constant) Incentive Opportunity Attitude Dependent Variable: Overall risk decision, S.E-Standard Error, **p<0.01 0.304 0.517 0.333 0.075 1.118 0.132 0.096 0.128 0.271 3.919 3.451 0.587 0.788 0.000** 0.001** 0.561 0.526 14.060 Table 59 presents the multiple regressions. The t-value and p-value for each independent variable tells whether the model is significantly predict the dependent variable or not. In this study, p-values are less than 0.05 for incentive (Beta=0.517, t=3.919, p<0.01) and opportunity (Beta=0.333, t=3.451, p<0.01) on overall risk decision in high risk, it reveals that two factors are used to predict the overall risk decision. Also the R-square value indicates 53 % of variation can be explained in the dependent variable that can be explained by these two factors. All the estimated values (β) are positive. Hence we concluded that, increasing the incentive and opportunity were associated with an increased overall risk decision. 49 © 2016-2017 All Rights Reserved, No part of this document should be modifed/used without prior consent Statswork™ - Your trusted mentor since 2001 I www.statswork.com UK: The Portergate, Ecclesall Road, Shefeld, S11 8NX I UK # +44-1143520021, Info@statswork.com

Comparison between two groups’ high skepticism auditors and low skepticism auditors| Statswork