1. 1 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Learning Objectives: 1. 1.Discuss hypothesis testing and why we use it. 2. 2.Explain the concept of statistical significance. 3. 3.Understand how to choose the appropriate statistical technique. 4. 4.Explain the difference between sample statistics and population parameters. 5. 5.Explain the difference between the t-test, ANOVA and Chi-square. Basic Data Analysis Methods Chapter 10

2. 2 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Hypothesis.... an unproven supposition or proposition that tentatively explains certain facts or phenomena.

3. 3 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Null vs. Alternative Hypotheses: Null hypothesis = no difference in group means. Alternative hypothesis = the opposite of the null hypothesis; i.e., there are differences in the group means.

4. 4 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Directional vs. Non-directional Hypotheses: Directional = a hypothesis that uses terms like more than, less than, positive or negative in stating the relationship between two groups or two variables. Non-directional = a hypothesis that postulates a difference, but does not indicate a direction for the differences or relationship.

5. 5 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Steps in Hypothesis Development and Testing: Step 1: State the null and alternative hypotheses. Step 2: Make a judgment about the population distribution, the level of measurement, and then select the appropriate statistical test. Step 3: Decide upon the desired level of significance. Step 4: Collect data from a sample and compute the statistical test to see if the level of significance is met. Step 5: Accept or reject the null hypothesis.

6. 6 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Sample Statistics vs. Population Parameters: Sample statistics = variables or measures computed from the sample. Population parameters = variables or measures of the population.

7. 7 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Go On-Line www.mathacademy.com/pr/index.asp Type I and Type II Error Type II Error = when the sample results lead to not rejecting the null hypothesis when it is in fact false. Type I Error = when the sample results lead to rejection of the null hypothesis when it is true.

8. 8 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. The choice of a particular technique depends upon: the number of variables. the scale of measurement. Choosing the Appropriate Statistical Technique:

9. 9 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Exhibit 10-1 Type of Scale and Appropriate Statistical Test Type of ScaleMeasure of Central Tendency Measure of Dispersion Statistical Test NominalModeNoneChi-Square OrdinalMedianPercentileChi-Square Interval or RatioMeanStandard Deviation T-test, ANOVA

10. 10 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Statistics on the World Wide Web Data and Story Library http://lib.stat.cmu.edu/DASL/ Documents Center at Univ. of Michigan http://www.lib.umich.edu/govdocs/stats.html Electronic Encyclopedia of Statistical Exercises & Examples http://lib.stat.cmu.edu/DASL/Reference/eesee.html Chance www.dartmouth.edu/~chance/teaching_aids/data.html

11. 11 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Statistics on the World Wide Web Journal of Statistics Education www.amstat.org/publications/jse/ Statistics.com http://www.berinsteinresearch.com/stats.html StatLib http://lib.stat.cmu.edu/ FEDSTATS http://www.fedstats.gov/

12. 12 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Statistics on the World Wide Web WebStat http://www.stat.sc.edu/webstat/ StatWeb http://www.statsci.org/

13. 13 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Go On-Line http://www.stat.sc.edu/webstat/ Parametric vs. Nonparametric Tests Nonparametric = no assumptions required about the distribution of the data and can be measured using a nominal or ordinal scale. Parametric = assume the sample data are normally distributed and measured using an interval or ratio scale.

14. 14 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Univariate Bivariate Multivariate Three Approaches to Statistically Analyzing Sample Data:

15. 15 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Examples of propositions that can be tested using univariate statistics: Employee satisfaction at Microsoft is at least 5.5 on a 7-point scale. The new product will be preferred by 90 percent of our current customers. The average monthly electric bill in Atlanta, Georgia exceeds $300.00. The market share for Community Coffee in south Louisiana is at least 70 percent. More than 50 percent of current Diet Coke customers will prefer the new Diet Coke that includes lemon taste.

16. 16 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Exhibit 10-2 One Sample T-Test of Samouel’s and Gino’s Prices X 25 – CompetitorVariableNMeanSD Samouel’sX 10 – Reasonable Prices 1004.14.932 Gino’sX 10 – Reasonable Prices 1003.97.937 One-Sample Statistics

17. 17 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Exhibit 10-2 One Sample T-Test of Samouel’s and Gino’s Prices Test Value = 5.0 tSig.Mean Difference X 25 – Competitor Samouel’sX 10 – Reasonable Prices -9.225.000-.86 Gino’sX 10 – Reasonable Prices -10.993.000-.103 One-Sample Test

18. 18 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Are gender and work type (full-time vs. part-time) at Samouel’s restaurant related? Do restaurant selection factor rankings (most important, 2nd most important, 3rd in importance, etc.) differ between males and females? Does frequency of patronage (very frequent, somewhat frequent and occasional) differ between Samouel’s and Gino’s restaurants? Is usage (heavy, moderate and low) of the Internet related to educational levels (elementary, middle, high school, some college, college degree, postgraduate work)? Is brand awareness (unaware, aware) related to the geographic area in which individuals live (North America, Europe, Asia, Africa, etc.)? Examples of questions that could be answered using cross tabulations and testing with Chi-square analysis:

19. 19 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Examples of questions that could be answered by testing differences in group means: Do the coffee consumption patterns (measured using the mean number of cups consumed daily) of males and females differ? Does the number of hours an individual spends on the Internet each week differ by income level? … by gender? … by education? Do younger workers exhibit higher job satisfaction than do older workers? Do big five accounting firms have a more favorable image than do regional accounting firms?

20. 20 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Independent vs. Related Samples Related Samples = when a sample of females is interviewed and the number of times a week they eat at Burger King ® is compared to the number of times they eat at McDonalds ®. Independent Samples = when a sample of males and females are interviewed and their consumption of cokes is compared. On Line http://www.burgerking.com http://www.mcdonalds.com

21. 21 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Exhibit 10-5 Testing Differences in Two Means Using the T-Test X 25 – CompetitorNMeanSD X 17 – Satisfaction Samouel’s1004.781.16 Gino’s1005.96.974 Group Statistics

22. 22 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Exhibit 10-5 Testing Differences in Two Means Using the T-Test t-test for Equality of MeansSig.Mean Difference t X 17 – Satisfaction Equal variances assumed -7.793.000-1.18 Equal variances not assumed -7.793.000-1.18 Independent Samples Test

23. 23 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. ANOVA.... is used to assess the statistical differences between the means of two or more groups of respondents.

24. 24 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Exhibit 10-6 Analysis of Variance Testing Mean Differences in Satisfaction Levels of Samoul’s Customers Based on Frequency of Patronage X 25 – Competitor X 20 – Frequency of Patronage MeanNSD Samouel’sOccasional Patron4.0447.69 Somewhat Frequent Patron 4.6221.80 Very Frequent Patron5.9732.93 Total4.781001.16 X 17 – Satisfaction

25. 25 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Exhibit 10-6 Analysis of Variance Testing Mean Differences in Satisfaction Levels of Samoul’s Customers Based on Frequency of Patronage X 25 – Competitor Sum of Squares FSig. Samouel’sX 17 – Satisfaction * X 20 – Frequency of Patronage 71.324 (between groups) 55.942.000 61.836 (within groups) Total133.160 ANOVA Table

26. 26 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Exhibit 10-6 Analysis of Variance Testing Mean Differences in Satisfaction Levels of Samouel’s Customers Based on Frequency of Patronage X 25 – Competitor Sum of Squares Mean Square FSig. Samouel’sX 17 – Satisfaction * X 20 – Frequency of Patronage 71.324 (between groups) 35.66255.942.000 61.836 (within groups).637 Total133.160 ANOVA Table

27. 27 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Exhibit 10-7 The Scheffe Test for Differences in Group Means X 25 – Competitor X 20 – Frequency of Patronage MeanN Samouel’sOccasional Patron4.0447 Somewhat Frequent Patron 4.6221 Very Frequent Patron5.9732 Total4.78100 X 17 – Satisfaction

28. 28 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Exhibit 10-7 The Scheffe Test for Differences in Group Means X 25 – Competitor X 20 – Frequency of Patronage MeanN Gino’sOccasional Patron4.789 Somewhat Frequent Patron 5.6929 Very Frequent Patron6.2662 Total5.96100 X 17 – Satisfaction

29. 29 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. One-Way vs. Two-Way ANOVA One-Way ANOVA = a single non-metric independent variable and a single metric dependent variable. Two-Way ANOVA = two or more non-metric independent variables and a single metric dependent variable.

30. 30 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Factorial Designs Factorial Designs, also referred to as two-way ANOVA, test three hypotheses: (1) the effect of independent variable one on the dependent variable; (2) the effect of independent variable two on the dependent variable; and (3) the combined (joint) effect of variables one and two on the dependent variable. The effects of the two independent variables are referred to as main effects, and their combined effect is referred to as the interaction effect.

31. 31 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. MANOVA MANOVA (multivariate analysis of variance) assesses group differences across multiple metric dependent variables at the same time.

32. 32 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Basic Data Analysis Methods Go On-Line www.yankelovich.com How can business researchers use the data from the research reported on these Web sites? Go On-Line www.raosoft.com

33. 33 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003. Basic Data Analysis Methods What can business researchers learn from these Web sites? Go On-Line www.surveysystem.com/sscalc.htm http://www.upromote.com Go On-Line www.dssresearch.com/mainsite/surveys.htm