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SPSS

APPENDIX 2 CONTOH PENYEDIAAN JADUAL DAN INTERPRETASI DATA. SPSS. Dr. Siti Nor Binti Yaacob. Quantitative Research. Quantitative Research. Data Entry. Varaible View. Data Transformation(recode data).

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SPSS

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  1. SITINORYAACOB/FEM4999B/2014/2015 APPENDIX 2 CONTOH PENYEDIAAN JADUAL DAN INTERPRETASI DATA SPSS Dr. Siti Nor Binti Yaacob

  2. SITINORYAACOB/FEM4999B/2014/2015 Quantitative Research

  3. SITINORYAACOB/FEM4999B/2014/2015 Quantitative Research

  4. SITINORYAACOB/FEM4999B/2014/2015 Data Entry Varaible View

  5. SITINORYAACOB/FEM4999B/2014/2015 Data Transformation(recode data) • TransformRecode Into Different Variable  “choose your item”  input variable --> renew the name in output variable (name and label)  Change. • Old and New Values  eg. 1 change to 5  add  continue  OK

  6. SITINORYAACOB/FEM4999B/2014/2015 Reliability test • Analyze  Scale  Reliability Analysis  choose all of the tested items • Scale label, type the name of variable . • Statistics  Choose “Item, Scale, and Scale if Item Deleted”. • Continue OK.

  7. SITINORYAACOB/FEM4999B/2014/2015 Descriptive Analysis • Step 1: Analyze  Descriptive Statistics  Frequencies… • Step 2: select the variables and click in the box

  8. SITINORYAACOB/FEM4999B/2014/2015 • Step 3: Click “statistics” and choose “ mean, median, std. deviation, variance, range, minimum and maximum”.  click “continue”

  9. SITINORYAACOB/FEM4999B/2014/2015 • Step 4: Click “OK”. • Step 5: Interpret output

  10. SITINORYAACOB/FEM4999B/2014/2015 Example of Descriptive Table:

  11. SITINORYAACOB/FEM4999B/2014/2015 Example of Interpretation: Respondents’ age • The respondents aged between 15 and 18 years old (Mean=16.09, SD.=0.670). Majority of the respondents (55.1%) were 16 years old.

  12. SITINORYAACOB/FEM4999B/2014/2015 Independent t-test • Step 1: Analyze  Compare Means  Independent Sample t-test

  13. SITINORYAACOB/FEM4999B/2014/2015 • Step 2: Choose tested variable and put “groups” into “Grouping Variable”. • Step 3: State “Define Groups” (e.g., male= 0; female=1)  continue

  14. SITINORYAACOB/FEM4999B/2014/2015 • Step 4: Click “OK” • Step 5: Output

  15. SITINORYAACOB/FEM4999B/2014/2015 Mean scores • Step 6: Interpret output • Based on F significant value of Levene’s test (Circle with red color), • If F Value is not significant (p≥.05), report t-value and p value [sig. (2-tailed)] from “equal variance assumed”. • if F Value is significant (p<.05), report t-value and p value [sig. (2-tailed)] from “equal variance not assumed”.

  16. SITINORYAACOB/FEM4999B/2014/2015 Example of t-test table: Example of Interpretation: • There was difference in internet addiction between male and female adolescents (t=3.489, p<.01). Male adolescents (mean= 55.42) were found to have higher level of internet addiction than female adolescents (mean= 47.29). • Null hypothesis was rejected. Note: You can add some related past studies to support the result.

  17. SITINORYAACOB/FEM4999B/2014/2015 One way ANOVA • Step 1: Analyze  Compare Means  One-Way Anova • Step 2: Choose “tested continuous variables into the “Dependent list”. • Step 3: Choose categorical variable into the “Factor”. • Step 4: Post Hoc  Tukey • Step 5: Options  Choose “Descriptive”. • Step 6: Continue  OK

  18. SITINORYAACOB/FEM4999B/2014/2015 Output

  19. SITINORYAACOB/FEM4999B/2014/2015

  20. SITINORYAACOB/FEM4999B/2014/2015 One way ANOVA- Interpretation

  21. SITINORYAACOB/FEM4999B/2014/2015 Chi-Square • Step 1: Analyze  Descriptive statistics  Crosstabs • Step 2: Row: “races”; Column: “internet access” • Step 3: Statistics  check “chi-square” & “contingency coefficient”  Continue  OK

  22. SITINORYAACOB/FEM4999B/2014/2015 Output of Chi-square

  23. SITINORYAACOB/FEM4999B/2014/2015 Output of Chi-square • A valid Chi-square will present the expected count of less than 5 in the table should not be more than 15.0% of the total number in the same row (Sirkin, 2005). X² • Not a valid chi-square model.

  24. SITINORYAACOB/FEM4999B/2014/2015 Interpretation • If there is a valid chi-square model: 28.8

  25. SITINORYAACOB/FEM4999B/2014/2015 Pearson Correlation • Step 1: Analyze  Correlate  Bivariate..

  26. SITINORYAACOB/FEM4999B/2014/2015 • Step 2: Select variables and click into “Variables” box then click “OK”

  27. SITINORYAACOB/FEM4999B/2014/2015 • Step 3: Interpret output

  28. SITINORYAACOB/FEM4999B/2014/2015 Example of Pearson correlation table: Example of interpretation: • The result showed that there was a significant positive correlation between loneliness and internet addiction (r= .213, p<.001). The direction of relationship indicated that respondents with higher loneliness score, tend to report higher internet addiction. Therefore, null hypothesis that there is no significant relationship between loneliness and internet addiction was rejected. Note: You can add some related past studies to support the results.

  29. SITINORYAACOB/FEM4999B/2014/2015 Multiple regression • Step 1: Analyze Regression  Linear. • Step 2: Choose dependent variable into “Dependent”. • Step 3: Choose independent variables into “Independent variables”. • Step 4: Statistics  Estimates, Confidence intervals, model fit, descriptives”. • Step 5: Continue OK.

  30. SITINORYAACOB/FEM4999B/2014/2015

  31. SITINORYAACOB/FEM4999B/2014/2015

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