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Business Statistics

Business Statistics. SPSS: A Summary & Review. Agenda. Homework Return bivariate analysis (Excel) Questions about either Excel exercise Comments about bivariate exercise Collect SPSS exercises SPSS Reminder: delete extraneous output Filtering data

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Business Statistics

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  1. Business Statistics SPSS: A Summary & Review

  2. Agenda • Homework • Return bivariate analysis (Excel) • Questions about either Excel exercise • Comments about bivariate exercise • Collect SPSS exercises • SPSS • Reminder: delete extraneous output • Filtering data • Copy/paste into Word or other applications • CrossTabs • Define categories • Example comparing Excel and SPSS • Inference (population mean) • Hypothesis test • Estimation

  3. Manipulating Data • Refer to exercises due 4/5/2002 • Salary analysis • Men versus women • Excel: filter, copy, paste, analyze • Now, let’s look at using SPSS • Filtering • Data | Select Cases | If . . . • Now do analysis • Unfilter: Data | Select Cases | All Cases . . .

  4. Analyzing Qualitative Data • Recall • Two types of data • Qualitative (Gender and Computer Usage) • Quantitative (Salary, Age, . . . ) • Ordinal data can be treated as either quantitative or qualitative; categories with numerical order; e.g., Education and Job Classification • Analyzing relationship between two quantitative variables: regression • Analyzing relationship between two qualitative variables: crosstabs

  5. Consider Gender versus Job Classification • Does “job level” depend upon gender? • Simple frequency tables • Doesn’t tell us about how these variables are related • Need to go further: crosstabulation • Review of crosstabs • Joint frequency: basis for developing the other three • Joint relative frequency (% of total) • Analyzing relationships • Multiplication rule • If independent, joint % = product of margin % values

  6. Using Excel’s PivotTable Feature for Crosstabs • Select the data, including headings • Click on Data | PivotTable • Click twice on Next • Click on Layout • Drag Gender to row • Drag Job to column • Drag either to data • Double click on data button • Select Count, then click on Options • In Show Data As, select % of Total • Click on OK • Click on OK • Click on Finish

  7. Using SPSS Crosstabs • Analyze | Descriptives | Crosstabs • Select row and column variables • Click on Cells button • Leave Observed checked for Counts • Check Total for Percentages • Resulting table corresponds to Excel PivotTable • Analyze • P(Level | Gender) = P(Level)? • P(Level & Gender) = P(Level) x P(Gender)?

  8. Inference: A Quick Review Population or Process Sample Statistic Parameter Inferences

  9. Estimation & Hypothesis Testing • Hypothesis testing • Start with an assumed population (or process) parameter • Gather data and see if the statistic is likely, given the assumption • Estimation • Start with a sample statistic • Use that statistic to create an interval estimate • The situation dictates which is appropriate (sometimes either is)

  10. Using SPSS for Statistical Inference • Univariate analysis • Inference about averages, not proportions • Hypothesis testing: • First, setup test (H0 & HA, a, sketch, decision rule) • Then: Analyze | Compare Means | One-Sample t Test • Estimation: Analyze | Descriptive Statistics | Explore • Relationship between two variables • Both quantitative: Analyze | Regression • Both qualitative: Analyze | Descriptive Statistics | Crosstabs • Quantitative dependent & qualitative independent: Analyze | Compare Means | One-Way ANOVA

  11. Homework • CrossTabs exercise • Job Level vs Education • Use • Excel • SPSS • Inference exercises with SPSS • Hypothesis test • Confidence interval estimates • Sample size determination

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