Abstract
In this part, we will discuss three types of bivariate statistics: first, an independent samples t-test measures if two groups of a continuous variable are different from one another; second, an f-test or ANOVA measures if several groups of one continuous variable are different from one another; third, a chi-square test gauges whether there are differences in a frequency table (i.e., two-by-two table or two-by-three table). Wherever possible we use money spent partying per week as the dependent variable. For the independent variables, we employ an appropriate explanatory variable from our sample survey.
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Reference
Park, H. (2009). Comparing group means: T-tests and one-way ANOVA using Stata, SAS, R, and SPSS. Working paper, The University Information Technology Services (UITS), Center for Statistical and Mathematical Computing, Indiana University.
Further Reading
Statistics Textbooks
Basically every introductory to statistics book covers bivariate statistics between categorical and continuous variables. The books I list here are just a short selection of possible textbooks. I have chosen these books because they are accessible and approachable and they do not use math excessively.
Brians, C. L. (2016). Empirical political analysis: Pearson new international edition coursesmart etextbook. London: Routledge (chapter 11). Provides a concise introduction into different types of means testing.
Macfie, B. P., & Nufrio, P. M. (2017). Applied statistics for public policy. New York: Routledge. This practical text provides students with the statistical tools needed to analyze data. It also shows through several examples how statistics can be used as a tool in making informed, intelligent policy decisions (part 2).
Walsh, A., & Ollenburger, J. C. (2001). Essential statistics for the social and behavioral sciences: A conceptual approach. Upper Saddle River: Prentice Hall (chapters 7–11). These chapters explain in rather simple forms the logic behind different types of statistical tests between categorical variables and provide real life examples.
Presenting Results in Publications
Morgan, S., Reichert, T., & Harrison, T. R. (2016). From numbers to words: Reporting statistical results for the social sciences. London: Routledge. This book complements introductory to statistics books. It shows scholars how they can present their test results in either visual or text form in an article or scholarly book
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Stockemer, D. (2019). Bivariate Statistics with Categorical Variables. In: Quantitative Methods for the Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-99118-4_7
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