Abstract
In this chapter, we look at an important dilemma that researchers face in conducting criminal justice research. Although they seek to make statements about populations, generally they collect data on samples drawn from such populations. Statistical inference provides a solution to this dilemma: it allows the researcher to make statements, or inferences, about the characteristics of a population from data collected from a sample drawn from the population. We begin our discussion of statistical inference by explaining the dilemma researchers face in making statements about populations from samples. We then examine the logic of statistical inference and the statistical risks associated with using this logic. You will be introduced to how null and research hypotheses are set up, how risks of error are assessed, and how levels of statistical significance are used to limit this error.
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Notes
- 1.
M. Maltz, “Deviating from the Mean: The Declining Significance of Significance,” Journal of Research in Crime and Delinquency 31 (1994): 434–463.
- 2.
Some statisticians prefer to call the research hypothesis the “alternative” hypothesis, because we can, in theory, choose any value as the null hypothesis, and not just the value of zero or no difference. The alternative hypothesis, in this case, can be defined as all other possible outcomes or values. For example, you could state in your null hypothesis that the professor’s grades are, on average, five points higher than those of other professors in the college. The alternative hypothesis would be that the professor’s grades are not, on average, five points higher than those of other professors.
- 3.
See Lawrence Sherman and David Weisburd, “General Deterrent Effects of Police Patrol in Crime ‘Hot Spots’: A Randomized Study,” Justice Quarterly 12:4 (1995): 625–648.
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Weisburd, D., Britt, C. (2014). The Logic of Statistical Inference: Making Statements About Populations from Sample Statistics. In: Statistics in Criminal Justice. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-9170-5_6
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DOI: https://doi.org/10.1007/978-1-4614-9170-5_6
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