Abstract
In criminal justice research, we are often interested in comparing the means or proportions in two samples of data, either two different groups, the same group across time (before/after), or two related samples (e.g., comparing twins). In this chapter, we will walk through using the independent sample t-test for two sample means, dependent sample t-test for two sample means, or z-test to compare means and proportions in R using data from the National Youth Survey, which is a nationally representative survey of 1725 American adolescents, aged 11–17, to gauge adolescents’ attitudes and behaviors on various topics, including school performance, family life, deviance, drug use, and peer influence.
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References
Elliott, D. S. (2008a). National youth survey [United States]: Wave I, 1976 [Data file]. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor]. Retrieved from https://doi.org/10.3886/ICPSR08375.v2.
Elliott, D. S. (2008b). National youth survey [United States]: Wave II, 1977 [Data file]. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor]. Retrieved from https://doi.org/10.3886/ICPSR08424.v2.
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Key Terms
- Dependent sample t -test
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A test of statistical significance that is used when two samples are not independent.
- Independent sample t -test
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A test of statistical significance that examines the difference observed between the means of two unrelated samples.
- Test for equality of variance
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An F-test used to assess the null hypothesis that the two population variances are equal.
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Wooditch, A., Johnson, N.J., Solymosi, R., Medina Ariza, J., Langton, S. (2021). Comparing Two-Sample Means or Proportions. In: A Beginner’s Guide to Statistics for Criminology and Criminal Justice Using R. Springer, Cham. https://doi.org/10.1007/978-3-030-50625-4_11
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DOI: https://doi.org/10.1007/978-3-030-50625-4_11
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