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Inferential Statistics for Hypothesis Testing

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Illustrating Statistical Procedures: Finding Meaning in Quantitative Data

Abstract

This chapter discusses and illustrates inferential statistics for hypothesis testing. The procedures and fundamental concepts reviewed in this chapter can help to accomplish the following goals: (1) evaluate the statistical and practical significance of the difference between a specific statistic (e.g. a proportion, a mean, a regression weight, or a correlation coefficient) and its hypothesised value in the population; and/or (2) evaluate the statistical and practical significance of the difference between some combination of statistics (e.g. group means) and some combination of their corresponding population parameters. Such comparisons/tests may be relatively simple or multivariate in nature. In this chapter, you will explore various procedures (e.g. t-tests, analysis of variance, multiple regression, multivariate analysis of variance and covariance, discriminant analysis, logistic regression) that can be employed in different hypothesis testing situations and research designs to inform the judgments of significance. You will also learn that statistical significance is not the only way to address hypotheses—practical significance (e.g., effect size) is almost always relevant as well; in some cases, even more relevant. Finally, you will explore several fundamental concepts dealing with the logic of statistical inference, the general linear model, research design, sampling and, for complex designs, the concept of interaction.

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References

References for Fundamental Concept V

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Useful Additional Reading for for Fundamental Concept VI

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References for Fundamental Concept VII

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Useful Additional Reading for Fundamental Concept VII

  • Edmonds, W. E., & Kennedy, T. D. (2013). An applied reference guide to research designs: Quantitative, qualitative and mixed methods. Los Angeles: Sage. Ch. 1–8.

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References for Fundamental Concept VIII

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Useful Additional Reading for Fundamental Concept VIII

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  • De Vaus, D. (2002). Analyzing social science data: 50 key problems in data analysis. London: Sage. Ch. 20, 21, 22 and 26.

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  • Fricker, R. D. (2008). Sampling methods for web and e-mail surveys. In N. Fielding, R. M. Lee, & G. Blank (Eds.), The Sage handbook of online research methods (pp. 195–217). London: Sage Publications.

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  • Glass, G. V., & Hopkins, K. D. (1996). Statistical methods in education and psychology (3rd ed.). Upper Saddle River: Pearson. Ch. 10.

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  • Scheaffer, R. L., Mendenhall, W., III, Ott, L., & Kerow, K. G. (2012). Elementary survey sampling (7th ed.). Boston: Brooks/Cole Cengage Learning.

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Reference for Procedure 7.1

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Useful Additional Reading for Procedure 7.1

  • Agresti, A. (2018). Statistical methods for the social sciences (5th ed.). Boston: Pearson. Ch. 8.

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  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 17.

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  • Argyrous, G. (2011). Statistics for research: With a guide to SPSS (3rd ed.). London: Sage. Ch. 23.

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  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Ch. 19, (Sections 19.1 to 19.3).

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  • George, D., & Mallery, P. (2019). IBM SPSS statistics 25 step by step: A simple guide and reference (15th ed.). New York: Routledge. Ch. 8.

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  • Hildebrand, D. K., Laing, J. D., & Rosenthal, H. (1977). The analysis of ordinal data. Beverly Hills: Sage.

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  • Liebetrau, A. M. (1983). Measures of association. Beverly Hills: Sage.

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  • Reynolds, H. T. (1984). Analysis of nominal data (2nd ed.). Beverly Hills: Sage.

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  • Smithson, M. J. (2000). Statistics with confidence. London: Sage. Ch. 9.

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  • Steinberg, W. J. (2011). Statistics alive (2nd ed.). Los Angeles: Sage. Ch. 31.

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Reference for for Procedure 7.2

  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Ch. 10 (sections 10.1 to 10.8 and 10.10).

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Useful Additional Reading for Procedure 7.2

  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 5.

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  • Argyrous, G. (2011). Statistics for research: With a guide to SPSS (3rd ed.). London: Sage. Ch. 18.

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  • George, D., & Mallery, P. (2019). IBM SPSS statistics 25 step by step: A simple guide and reference (15th ed.). New York: Routledge. Ch. 11.

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  • Glass, G. V., & Hopkins, K. D. (1996). Statistical methods in education and psychology (3rd ed.). Upper Saddle River: Pearson. Ch. 12.

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  • Gravetter, F. J., & Wallnau, L. B. (2017). Statistics for the behavioural sciences (10th ed.). Belmont: Wadsworth Cengage. Ch. 10.

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  • Howell, D. C. (2013). Statistical methods for psychology (8th ed.). Belmont: Cengage Wadsworth. Ch. 7.

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  • Rosenthal, R., & Rosnow, R. L. (1991). Essentials of behavioral research: Methods and data analysis (2nd ed.). New York: McGraw-Hill. Ch. 15.

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  • Steinberg, W. J. (2011). Statistics alive (2nd ed.). Los Angeles: Sage. Ch. 20–21, 23.

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Reference for for Procedure 7.3

  • Siegel, S., & Castellan, N. J., Jr. (1988). Nonparametric statistics (2nd ed., pp. 128–137). New York: McGraw-Hill. Ch. 6.

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Useful Additional Reading for Procedure 7.3

  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 17.

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  • Argyrous, G. (2011). Statistics for research: With a guide to SPSS (3rd ed.). London: Sage. Ch. 25.

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  • Corder, G. W., & Foreman, D. I. (2009). Nonparametric statistics for non-statisticians: A step-by-step approach. Hoboken: Wiley. Ch. 4.

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  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Ch. 7, Sections 7.1 to 7.4.

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  • Gibbons, J. D. (1993). Nonparametric statistics: An introduction. Beverly Hills: Sage. Ch. 4.

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  • Glass, G. V., & Hopkins, K. D. (1996). Statistical methods in education and psychology (3rd ed.). Upper Saddle River: Pearson. Ch. 12.

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  • Howell, D. C. (2013). Statistical methods for psychology (8th ed.). Belmont: Cengage Wadsworth. Ch. 18.

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  • Neave, H. R., & Worthington, P. L. (1988). Distribution-free statistics. London: Unwin Hyman. Ch. 5, 6, and 7.

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Reference for Procedure 7.4

  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Ch. 10, Sections 10.9 to 10.11.

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Useful Additional Reading for Procedure 7.4

  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 6.

    Google Scholar 

  • Argyrous, G. (2011). Statistics for research: With a guide to SPSS (3rd ed.). London: Sage. Ch. 20.

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  • George, D., & Mallery, P. (2019). IBM SPSS statistics 25 step by step: A simple guide and reference (15th ed.). New York: Routledge. Ch. 11.

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  • Glass, G. V., & Hopkins, K. D. (1996). Statistical methods in education and psychology (3rd ed.). Upper Saddle River: Pearson. Ch. 12.

    Google Scholar 

  • Gravetter, F. J., & Wallnau, L. B. (2017). Statistics for the behavioural sciences (10th ed.). Belmont: Wadsworth Cengage. Ch. 11.

    Google Scholar 

  • Howell, D. C. (2013). Statistical methods for psychology (8th ed.). Belmont: Cengage Wadsworth. Ch. 7.

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  • Rosenthal, R., & Rosnow, R. L. (1991). Essentials of behavioral research: Methods and data analysis (2nd ed.). New York: McGraw-Hill. Ch. 15.

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  • Steinberg, W. J. (2011). Statistics alive (2nd ed.). Los Angeles: Sage. Ch. 22.

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Reference for Procedure 7.5

  • Siegel, S., & Castellan, N. J., Jr. (1988). Nonparametric statistics (2nd ed., pp. 87–95). New York,. Ch. 5: McGraw-Hill.

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Useful Additional Reading for Procedure 7.5

  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 17.

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  • Argyrous, G. (2011). Statistics for research: With a guide to SPSS (3rd ed.). London: Sage. Ch. 25.

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  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Ch. 6, Section 7.5.

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  • Gibbons, J. D. (1993). Nonparametric statistics: An introduction. Beverly Hills: Sage. Ch. 3.

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  • Glass, G. V., & Hopkins, K. D. (1996). Statistical methods in education and psychology (3rd ed.). Upper Saddle River: Pearson. Ch. 12.

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  • Howell, D. C. (2013). Statistical methods for psychology (8th ed.). Belmont: Cengage Wadsworth. Ch. 18.

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  • Neave, H. R., & Worthington, P. L. (1988). Distribution-free statistics. London: Unwin Hyman. Ch. 8.

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References for Procedure 7.6

  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Ch. 12.

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  • Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. London: Sage. Ch. 10.

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  • Iversen, G. R., & Norpoth, H. (1987). Analysis of variance (2nd ed.). Newbury Park: Sage. Ch. 2 and 4.

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Useful Additional Reading for Procedure 7.6

  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 7.

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  • Argyrous, G. (2011). Statistics for research: With a guide to SPSS (3rd ed.). London: Sage. Ch. 19.

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  • Everitt, B. S. (1995). Making sense of statistics in psychology: A second level course. Oxford: Oxford University Press. Ch. 3.

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  • George, D., & Mallery, P. (2019). IBM SPSS statistics 25 step by step: A simple guide and reference (15th ed.). New York: Routledge. Ch. 8.

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  • Glass, G. V., & Hopkins, K. D. (1996). Statistical methods in education and psychology (3rd ed.). Upper Saddle River: Pearson. Ch. 15.

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  • Gravetter, F. J., & Wallnau, L. B. (2017). Statistics for the behavioural sciences (10th ed.). Belmont: Wadsworth Cengage. Ch. 12.

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  • Howell, D. C. (2013). Statistical methods for psychology (8th ed.). Belmont: Cengage Wadsworth. Ch. 11.

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  • Rosenthal, R., & Rosnow, R. L. (1991). Essentials of behavioral research: Methods and data analysis (2nd ed.). New York: McGraw-Hill. Ch. 15.

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  • Steinberg, W. J. (2011). Statistics alive (2nd ed.). Los Angeles: Sage. Ch. 24 and 25.

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References for Procedure 7.7

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale: Lawrence Erlbaum Associates.

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  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Ch. 12, Sections 12.10; see also ch. 7, sections 7.4.5, 7.5.5 and 7.6.7.

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  • Hays, W. L. (1988). Statistics (3rd ed.). New York: Holt, Rinehart, & Winston. Ch. 8, pp. 306–313; Ch. 10, p. 369 and pp. 374–376.

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  • Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). New York: Pearson Education. Ch. 3, Section 3.4.

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Useful Additional Reading for Procedure 7.7

  • Cortina, J., & Nouri, H. (2000). Effect size for ANOVA designs. Thousand Oaks: Sage.

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  • Keppel, G., & Wickens, T. D. (2004). Design and analysis: A researcher's handbook (4th ed.). Upper Saddle River: Prentice Hall. Ch. 8.

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  • Rosenthal, R., & Rosnow, R. L. (1991). Essentials of behavioral research: Methods and data analysis (2nd ed.). New York: McGraw-Hill. Ch. 15, pp. 317–318; Ch. 16, pp. 351–352.

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References for Procedure 7.8

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  • Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. London: Sage. Ch. 10.

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  • Keppel, G., & Wickens, T. D. (2004). Design and analysis: A researcher’s handbook (4th ed.). Upper Saddle River: Prentice Hall. Ch. 4, 5 and 6.

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  • Klockars, A. (1986). Multiple comparisons. Beverly Hills: Sage.

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  • Toothaker, L. E. (1993). Multiple comparison procedures. Newbury Park: Sage.

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Useful Additional Reading for Procedure 7.8

  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Section 12.5 and 12.6.

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  • Howell, D. C. (2013). Statistical methods for psychology (8th ed.). Belmont: Cengage Wadsworth. Ch. 12.

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  • Rosenthal, R., & Rosnow, R. L. (1991). Essentials of behavioral research: Methods and data analysis (2nd ed.). New York: McGraw-Hill. Ch. 21.

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  • Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). New York: Pearson Education. Ch. 3.

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References for Procedure 7.9

  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Section 7.6.

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  • Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R (pp. 674–686). London,. Ch. 15: Sage.

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  • Siegel, S., & Castellan, N. J., Jr. (1988). Nonparametric statistics (2nd ed.). New York: McGraw-Hill. Ch. 8, which also discusses multiple comparison methods.

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Useful Additional Reading for Procedure 7.9

  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 17.

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  • Argyrous, G. (2011). Statistics for research: With a guide to SPSS (3rd ed.). London: Sage. Ch. 25.

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  • Gibbons, J. D. (1993). Nonparametric statistics: An introduction. Beverly Hills: Sage.

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  • Howell, D. C. (2013). Statistical methods for psychology (8th ed.). Belmont: Cengage Wadsworth. Ch. 18.

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  • Neave, H. R., & Worthington, P. L. (1988). Distribution-free statistics. London: Unwin Hyman. Ch. 13, which also discusses multiple comparison methods.

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References for Procedure 7.10

  • Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah: Lawrence Erlbaum Associates. Ch. 5, 6, 8 and 9.

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  • Cooksey, R. W., & McDonald, G. (2019). Surviving and thriving in postgraduate research (2nd ed.). Singapore: Springer. Ch. 14, section 14.3.2 and pp. 676–677.

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  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Ch. 14.

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  • Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. London: Sage. Ch. 12.

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  • Judd, C. M., McClelland, G. H., & Ryan, C. S. (2017). Data analysis: A model-comparison approach (3rd ed.). New York: Routledge. Ch. 9.

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  • Keppel, G., & Wickens, T. D. (2004). Design and analysis: A researcher’s handbook (4th ed.). Upper Saddle River: Prentice Hall. Ch. 10, 11, 12, 13, 14, 21, 22, 25 and 26.

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  • Kirk, R. E. (2013). Experimental design: Procedures for behavioral sciences (4th ed.). Thousand Oaks: Sage. Ch. 6, 9, 10 and 11.

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Useful Additional Reading for Procedure 7.10

  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 8.

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  • Brown, S. R., & Melamed, L. E. (1990). Experimental design and analysis. Newbury Park: Sage.

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  • George, D., & Mallery, P. (2019). IBM SPSS statistics 25 step by step: A simple guide and reference (15th ed.). New York: Routledge. Ch. 8.

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  • Gravetter, F. J., & Wallnau, L. B. (2017). Statistics for the behavioural sciences (10th ed.). Belmont: Wadsworth Cengage. Ch. 14.

    Google Scholar 

  • Howell, D. C. (2013). Statistical methods for psychology (8th ed.). Belmont: Cengage Wadsworth. Ch. 13.

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  • Rosenthal, R., & Rosnow, R. L. (1991). Essentials of behavioral research: Methods and data analysis (2nd ed.). New York: McGraw-Hill. Ch. 16 and 17.

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References for Fundamental Concept IX

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  • Hayes, A. F. (2018). Introduction to mediation, moderation and conditional process analysis: A regression-based approach (3rd ed.). New York: The Guilford Press. Ch. 7.

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  • Keppel, G., & Wickens, T. D. (2004). Design and analysis: A researcher’s handbook (4th ed.). Upper Saddle River: Prentice Hall. Ch. 12 and 13.

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  • Miles, J., & Shevlin, M. (2001). Applying regression & correlation: A guide for students and researchers. Los Angeles: Sage. Ch. 7.

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Useful Additional Reading for Fundamental Concept IX

  • Brown, S. R., & Melamed, L. E. (1990). Experimental design and analysis. Newbury Park: Sage.

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  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Sections 14.6 and 14.7.

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  • Jose, P. E. (2013). Doing statistical mediation and moderation. New York: The Guilford Press.

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References for Procedure 7.11

  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Ch. 15 and 16.

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  • Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. London: Sage. Ch. 12.

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  • Keppel, G., & Wickens, T. D. (2004). Design and analysis: A researcher’s handbook (4th ed.). Upper Saddle River: Prentice Hall. Ch. 16–20, 23.

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  • Kirk, R. E. (2013). Experimental design: Procedures for behavioral sciences (4th ed.). Thousand Oaks: Sage. Ch. 10 and 12.

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  • Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). New York: Pearson Education. Ch. 8.

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  • Polhemus, N. W. (2006). How to: Analyze a repeated measures experiment using STATGRAPHICS Centurion. Document downloaded from http://cdn2.hubspot.net/hubfs/402067/PDFs/How_To_Analyze_a_Repeated_Measures_Experiment.pdf. Accessed 1 Oct 2019.

Useful Additional Reading for Procedure 7.11

  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 9.

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  • Brown, S. R., & Melamed, L. E. (1990). Experimental design and analysis. Newbury Park: Sage.

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  • Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah: Lawrence Erlbaum Associates. Ch. 15.

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  • George, D., & Mallery, P. (2019). IBM SPSS statistics 25 step by step: A simple guide and reference (15th ed.). New York: Routledge. Ch. 8.

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  • Girden, E. R. (1992). ANOVA repeated measures. Newbury Park: Sage.

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  • Gravetter, F. J., & Wallnau, L. B. (2017). Statistics for the behavioural sciences (10th ed.). Belmont: Wadsworth Cengage. Ch. 14.

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  • Grimm, L. G., & Yarnold, P. R. (Eds.). (2000). Reading and understanding more multivariate statistics. Washington, DC: American Psychological Association (APA). Ch. 10.

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  • Howell, D. C. (2013). Statistical methods for psychology (8th ed.). Belmont: Cengage Wadsworth. Ch. 14.

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  • Judd, C. M., McClelland, G. H., & Ryan, C. S. (2017). Data analysis: A model-comparison approach (3rd ed.). New York: Routledge. Ch. 11.

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  • Rosenthal, R., & Rosnow, R. L. (1991). Essentials of behavioral research: Methods and data analysis (2nd ed.). New York: McGraw-Hill. Ch. 18.

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References for Procedure 7.12

  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Section 7.7.

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  • Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R (pp. 686–692). London,. Ch. 15: Sage.

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  • Siegel, S., & Castellan, N. J., Jr. (1988). Nonparametric statistics (2nd ed.). New York: McGraw-Hill. Ch. 7, which also discusses multiple comparison methods.

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Useful Additional Reading for Procedure 7.12

  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 17.

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  • Gibbons, J. D. (1993). Nonparametric statistics: An introduction. Beverly Hills: Sage.

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  • Howell, D. C. (2013). Statistical methods for psychology (8th ed.). Belmont: Cengage Wadsworth. Ch. 18.

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  • Neave, H. R., & Worthington, P. L. (1988). Distribution-free statistics. London: Unwin Hyman. Ch. 14, which also discusses multiple comparison methods.

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References for Procedure 7.13

  • Berry, W. (1993). Understanding regression assumptions. Beverly Hills: Sage.

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  • Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah: Lawrence Erlbaum Associates. Ch. 3, 4, 5, 6–9, 10 provide comprehensive coverage of multiple regression concepts at a good conceptual and technical level].

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  • Dunteman, G. (2005). Introduction to generalized linear models. Thousand Oaks: Sage.

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  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Ch. 6 and 9.

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  • Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. London: Sage. Ch. 7.

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  • Fox, J. (1991). Regression diagnostics: An introduction. Beverly Hills: Sage.

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  • Fox, J. (2000). Multiple and generalized nonparametric regression. Thousand Oaks: Sage.

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  • Gill, J. (2000). Generalized linear models: A unified approach. Thousand Oaks: Sage.

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  • Hair, J. F., Black, B., Babin, B., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Upper Saddle River: Pearson Education. Ch. 4.

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  • Judd, C. M., McClelland, G. H., & Ryan, C. S. (2017). Data analysis: A model-comparison approach (3rd ed.). New York: Routledge. Ch. 6.

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  • Lewis-Beck, M. S. (1980). Applied regression: An introduction. Newbury Park: Sage.

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  • Miles, J., & Shevlin, M. (2001). Applying regression & correlation: A guide for students and researchers. London: Sage. Ch. 2–7 provide comprehensive coverage of multiple regression concepts at a good conceptual level.

    Google Scholar 

  • Pedhazur, E. J. (1997). Multiple regression in behavioral research: Explanation and prediction (3rd ed.). South Melbourne: Wadsworth Thomson Learning. Ch. 3, 5–15 provide comprehensive coverage of multiple regression concepts at a more technical level.

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Useful Additional Reading for Procedure 7.13

  • Agresti, A. (2018). Statistical methods for the social sciences (5th ed.). Boston: Pearson. Ch. 12.

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  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 13.

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  • Darlington, R. B., & Hayes, A. F. (2017). Regression analysis and linear models: Concepts, applications, and implementation. New York: The Guilford Press.

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  • Grimm, L. G., & Yarnold, P. R. (1995). Reading and understanding multivariate statistics. Washington, DC: American Psychological Association. Ch. 2.

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  • Hardy, M. (1993). Regression with dummy variables. Thousand Oaks: Sage.

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  • Howell, D. C. (2013). Statistical methods for psychology (8th ed.). Belmont: Cengage Wadsworth. Ch. 15.

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  • George, D., & Mallery, P. (2019). IBM SPSS statistics 25 step by step: A simple guide and reference (15th ed.). New York: Routledge. Ch. 16 and 28.

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  • Meyers, L. S., Gamst, G. C., & Guarino, A. (2017). Applied multivariate research: Design and interpretation (3rd ed.). Thousand Oaks: Sage. Ch. 5A, 5B, 6A, 6B.

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  • Schroeder, L. D., Sjoquist, D. L., & Stephan, P. E. (1986). Understanding regression analysis: An introductory guide. Beverly Hills: Sage.

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  • Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). New York: Pearson Education. Ch. 5.

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References for Procedure 7.14

  • Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah: Lawrence Erlbaum Associates. Ch. 13.

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  • Everitt, B. S., & Hothorn, T. (2006). A handbook of statistical analyses using R. Boca Raton: Chapman & Hall/CRC.

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  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Ch. 20.

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  • Miles, J., & Shevlin, M. (2001). Applying regression & correlation: A guide for students and researchers. London: Sage. Ch. 6.

    Google Scholar 

  • Pedhazur, E. J. (1997). Multiple regression in behavioral research: Explanation and prediction (3rd ed.). South Melbourne: Wadsworth Thomson Learning. Ch. 17.

    MATH  Google Scholar 

  • Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). New York: Pearson Education. Ch. 10.

    Google Scholar 

Useful Additional Reading for Procedure 7.14

  • Agresti, A. (2018). Statistical methods for the social sciences (5th ed.). Boston: Pearson. Ch. 13.

    Google Scholar 

  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 14.

    Google Scholar 

  • Grimm, L. G., & Yarnold, P. R. (Eds.). (1995). Reading and understanding multivariate statistics. Washington, DC: American Psychological Association (APA). Ch. 7.

    Google Scholar 

  • George, D., & Mallery, P. (2019). IBM SPSS statistics 25 step by step: A simple guide and reference (15th ed.). New York: Routledge. Ch. 25.

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  • Hair, J. F., Black, B., Babin, B., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Upper Saddle River: Pearson Education. Ch. 7.

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  • Menard, S. (2002). Applied logistic regression analysis (2nd ed.). Thousand Oaks: Sage.

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  • Meyers, L. S., Gamst, G. C., & Guarino, A. (2017). Applied multivariate research: Design and interpretation (3rd ed.). Thousand Oaks: Sage. Ch. 9A, 9B.

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  • Pampel, F. (2000). Logistic regression: A primer. Thousand Oaks: Sage.

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References for Procedure 7.15

  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Ch. 13.

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  • Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. London: Sage. Ch. 11.

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  • Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). New York: Pearson Education. Ch. 6.

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  • Wildt, A. R., & Ahtola, O. T. (1978). Analysis of covariance. Beverly Hills: Sage.

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Useful Additional Reading for Procedure 7.15

  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 10.

    Google Scholar 

  • Judd, C. M., McClelland, G. H., & Ryan, C. S. (2017). Data analysis: A model-comparison approach (3rd ed.). New York: Routledge. Ch. 10.

    Book  Google Scholar 

  • Keppel, G., & Wickens, T. D. (2004). Design and analysis: A researcher’s handbook (4th ed.). Upper Saddle River: Prentice Hall. Ch. 15.

    Google Scholar 

  • Kirk, R. E. (2013). Experimental design: Procedures for behavioral sciences (4th ed.). Thousand Oaks: Sage. Ch. 13.

    Book  MATH  Google Scholar 

  • Pedhazur, E. J. (1997). Multiple regression in behavioral research: Explanation and prediction (3rd ed.). South Melbourne: Wadsworth Thomson Learning. Ch. 15.

    MATH  Google Scholar 

References for Procedure 7.16

  • Bray, J. H., & Maxwell, S. E. (1985). Multivariate analysis of variance. Beverly Hills: Sage.

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  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Ch. 17.

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  • Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. London: Sage. Ch. 16.

    Google Scholar 

  • Hair, J. F., Black, B., Babin, B., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Upper Saddle River: Pearson Education. Ch. 8.

    Google Scholar 

  • Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). New York: Pearson Education. Ch. 7.

    Google Scholar 

Useful Additional Reading for Procedure 7.16

  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 11.

    Google Scholar 

  • George, D., & Mallery, P. (2019). IBM SPSS statistics 25 step by step: A simple guide and reference (15th ed.). New York: Routledge. Ch. 23.

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  • Grimm, L. G., & Yarnold, P. R. (1995). Reading and understanding multivariate statistics. Washington, DC: American Psychological Association. Ch. 8.

    Google Scholar 

  • Meyers, L. S., Gamst, G. C., & Guarino, A. (2017). Applied multivariate research: Design and interpretation (3rd ed.). Thousand Oaks: Sage. Ch. 18A, 18B.

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References for Procedure 7.17

  • Hair, J. F., Black, B., Babin, B., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Upper Saddle River: Pearson Education. Ch. 7.

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  • Huberty, C. J. (1984). Issues in the use and interpretation of discriminant analysis. Psychological Bulletin, 95(1), 156–171.

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  • Klecka, W. R. (1980). Discriminant analysis. Beverly Hills: Sage.

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  • Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). New York: Pearson Education. Ch. 9.

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Useful Additional Reading for Procedure 7.17

  • Allen, P., Bennett, K., & Heritage, B. (2019). SPSS statistics: A practical guide (4th ed.). South Melbourne: Cengage Learning Australia Pty. Ch. 11.

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  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Sections 17.9 to 17.11.

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  • Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. London: Sage. Ch. 16.

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  • George, D., & Mallery, P. (2019). IBM SPSS statistics 25 step by step: A simple guide and reference (15th ed.). New York: Routledge. Ch. 22.

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  • Grimm, L. G., & Yarnold, P. R. (1995). Reading and understanding multivariate statistics. Washington, DC: American Psychological Association. Ch. 9.

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  • Lohnes, P. R. (1997). Discriminant analysis. In J. P. Keeves (Ed.), Educational research, methodology, and measurement: An international handbook (2nd ed., pp. 503–508). Oxford: Pergamon Press.

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  • Meyers, L. S., Gamst, G. C., & Guarino, A. (2017). Applied multivariate research: Design and interpretation (3rd ed.). Thousand Oaks: Sage. Ch. 19A, 19B.

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References for Procedure 7.18

  • Anderton, D. L., & Cheney, E. (2004). Log-linear analysis. In M. Hardy & A. Bryman (Eds.), Handbook of data analysis (pp. 285–306). London: Sage.

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  • Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. London: Sage. Ch. 18.

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  • Knoke, D., & Burke, P. J. (1980). Log-linear models. Beverly Hills: Sage.

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  • Norušis, M. J. (2012). IBM SPSS Statistics 19: Advanced statistical procedures companion. Upper Saddle River: Prentice Hall. Ch. 1 and 2.

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  • Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). New York: Pearson Education. Ch. 16.

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Useful Additional Reading for Procedure 7.18

  • Everitt, B. S. (1977). The analysis of contingency tables. New York: Wiley. Ch. 5.

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  • Field, A. (2018). Discovering statistics using SPSS for Windows (5th ed.). Los Angeles: Sage. Section 19.9 to 19.11.

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  • George, D., & Mallery, P. (2019). IBM SPSS statistics 25 step by step: A simple guide and reference (15th ed.). New York: Routledge. Ch. 26 and 27.

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  • Grimm, L. G., & Yarnold, P. R. (1995). Reading and understanding multivariate statistics. Washington, DC: American Psychological Association. Ch. 6.

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  • Kennedy, J. J., & Tam, H. K. (1997). Log-linear models. In J. P. Keeves (Ed.), Educational research, methodology, and measurement: An international handbook (2nd ed., pp. 571–580). Oxford: Pergamon Press.

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  1. UNE Business School, University of New England, Armidale, NSW, Australia

    Ray W. Cooksey

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Cooksey, R.W. (2020). Inferential Statistics for Hypothesis Testing. In: Illustrating Statistical Procedures: Finding Meaning in Quantitative Data . Springer, Singapore. https://doi.org/10.1007/978-981-15-2537-7_7

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