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Research Methods for Business Research Methods for Business 1 Chapter 15 Quantitative Data Analysis: Hypothesis Testing © 2012 John Wiley & Sons Ltd. www.wiley.com/college/sekaran.

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Presentation on theme: "Research Methods for Business Research Methods for Business 1 Chapter 15 Quantitative Data Analysis: Hypothesis Testing © 2012 John Wiley & Sons Ltd. www.wiley.com/college/sekaran."— Presentation transcript:

1 Research Methods for Business Research Methods for Business 1 Chapter 15 Quantitative Data Analysis: Hypothesis Testing © 2012 John Wiley & Sons Ltd.

2 Research Methods for Business Type I Errors, Type II Errors and Statistical Power Type I error (  ): the probability of rejecting the null hypothesis when it is actually true. Type II error (  ): the probability of failing to reject the null hypothesis given that the alternative hypothesis is actually true. Statistical power (1 -  ): the probability of correctly rejecting the null hypothesis. © 2012 John Wiley & Sons Ltd.

3 Research Methods for Business Choosing the Appropriate Statistical Technique © 2012 John Wiley & Sons Ltd.

4 Research Methods for Business Testing Hypotheses on a Single Mean One sample t-test: statistical technique that is used to test the hypothesis that the mean of the population from which a sample is drawn is equal to a comparison standard. © 2012 John Wiley & Sons Ltd.

5 Research Methods for Business Testing Hypotheses about Two Related Means Paired samples t-test: examines differences in same group before and after a treatment. The Wilcoxon signed-rank test: a non- parametric test for examining significant differences between two related samples or repeated measurements on a single sample. Used as an alternative for a paired samples t- test when the population cannot be assumed to be normally distributed. © 2012 John Wiley & Sons Ltd.

6 Research Methods for Business Testing Hypotheses about Two Related Means - 2 McNemar's test: non-parametric method used on nominal data. It assesses the significance of the difference between two dependent samples when the variable of interest is dichotomous. It is used primarily in before- after studies to test for an experimental effect. © 2012 John Wiley & Sons Ltd.

7 Research Methods for Business Testing Hypotheses about Two Unrelated Means Independent samples t-test: is done to see if there are any significant differences in the means for two groups in the variable of interest. © 2012 John Wiley & Sons Ltd.

8 Research Methods for Business Testing Hypotheses about Several Means ANalysis Of VAriance (ANOVA) helps to examine the significant mean differences among more than two groups on an interval or ratio-scaled dependent variable. © 2012 John Wiley & Sons Ltd.

9 Research Methods for Business Regression Analysis Simple regression analysis is used in a situation where one metric independent variable is hypothesized to affect one metric dependent variable. © 2012 John Wiley & Sons Ltd.

10 Research Methods for Business Research Methods for Business Scatter plot © 2012 John Wiley & Sons Ltd.

11 Research Methods for Business Research Methods for Business Simple Linear Regression Y X `0  1 © 2012 John Wiley & Sons Ltd.

12 Research Methods for Business Research Methods for Business Ordinary Least Squares Estimation YiYi XiXi YiYi eiei ˆ © 2012 John Wiley & Sons Ltd.

13 Research Methods for Business SPSS Analyze  Regression  Linear © 2012 John Wiley & Sons Ltd.

14 Research Methods for Business SPSS cont’d © 2012 John Wiley & Sons Ltd.

15 Research Methods for Business Model validation 1.Face validity: signs and magnitudes make sense 2.Statistical validity: – Model fit: R 2 – Model significance: F-test – Parameter significance: t-test – Strength of effects: beta-coefficients – Discussion of multicollinearity: correlation matrix 3.Predictive validity: how well the model predicts – Out-of-sample forecast errors © 2012 John Wiley & Sons Ltd.

16 Research Methods for Business SPSS © 2012 John Wiley & Sons Ltd.

17 Research Methods for Business Measure of Overall Fit: R 2 R 2 measures the proportion of the variation in y that is explained by the variation in x. R 2 = total variation – unexplained variation total variation R 2 takes on any value between zero and one: – R 2 = 1: Perfect match between the line and the data points. – R 2 = 0: There is no linear relationship between x and y. © 2012 John Wiley & Sons Ltd.

18 Research Methods for Business SPSS = r(Likelihood to Date, Physical Attractiveness) © 2012 John Wiley & Sons Ltd.

19 Research Methods for Business Model Significance H 0 :  0 =  1 =... =  m = 0 (all parameters are zero) H 1 : Not H 0 © 2012 John Wiley & Sons Ltd.

20 Research Methods for Business Model Significance H 0 :  0 =  1 =... =  m = 0 (all parameters are zero) H 1 : Not H 0 Test statistic (k = # of variables excl. intercept) F = (SS Reg /k) ~ F k, n-1-k (SS e /(n – 1 – k) SS Reg = explained variation by regression SS e = unexplained variation by regression © 2012 John Wiley & Sons Ltd.

21 Research Methods for Business SPSS © 2012 John Wiley & Sons Ltd.

22 Research Methods for Business Parameter significance Testing that a specific parameter is significant (i.e.,  j  0) H 0 :  j = 0 H 1 :  j  0 Test-statistic: t = b j /SE j ~ t n-k-1 with b j = the estimated coefficient for  j SE j = the standard error of b j © 2012 John Wiley & Sons Ltd.

23 Research Methods for Business SPSS cont’d © 2012 John Wiley & Sons Ltd.

24 Research Methods for Business Conceptual Model Physical Attractiveness Likelihood to Date +

25 Research Methods for Business Multiple Regression Analysis We use more than one (metric or non-metric) independent variable to explain variance in a (metric) dependent variable.

26 Research Methods for Business Conceptual Model Perceived Intelligence Physical Attractiveness + + Likelihood to Date

27 Research Methods for Business Research Methods for Business

28 Research Methods for Business Conceptual Model Perceived Intelligence Physical Attractiveness Likelihood to Date Gender + + +

29 Research Methods for Business Moderators Moderator is qualitative (e.g., gender, race, class) or quantitative (e.g., level of reward) that affects the direction and/or strength of the relation between dependent and independent variable Analytical representation Y = ß 0 + ß 1 X 1 + ß 2 X 2 + ß 3 X 1 X 2 with Y = DV X 1 = IV X 2 = Moderator

30 Research Methods for Business Research Methods for Business

31 Research Methods for Business Research Methods for Business interaction significant effect on dep. var.

32 Research Methods for Business Conceptual Model Perceived Intelligence Physical Attractiveness Communality of Interests Likelihood to Date Gender Perceived Fit

33 Research Methods for Business Mediating/intervening variable Accounts for the relation between the independent and dependent variable Analytical representation 1.Y = ß 0 + ß 1 X => ß 1 is significant 2.M = ß 2 + ß 3 X => ß 3 is significant 3.Y = ß 4 + ß 5 X + ß 6 M => ß 5 is not significant => ß 6 is significant WithY = DV X = IV M = mediator

34 Research Methods for Business Step 1

35 Research Methods for Business Step 1 cont’d significant effect on dep. var.

36 Research Methods for Business Step 2

37 Research Methods for Business Step 2 cont’d significant effect on mediator

38 Research Methods for Business Research Methods for Business Step 3

39 Research Methods for Business Research Methods for Business Step 3 cont’d significant effect of mediator on dep. var. insignificant effect of indep. var on dep. Var.


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