Brief Introduction of Statistics in Criminal Justice

Criminological research is developing by leaps and bounds. Huge amounts of data are collected by both scientists studying issues of crime and justice as well as by those working in the day-to-day administration of the criminal justice system. It would be impossible to summarize all of this information in a timely fashion without the help of statistical analysis.

Statistics are based on a basic mathematical principle known as probability theory. This theory is predicated on illustrating the odds, or probability, of something occurring. Therefore, statistics are a mathematical expression of likelihood, such as the likelihood of inner-city children becoming gang members, the likelihood of probationers to recidivate, etc.

So what, specifically, are statistics able to do?

First, statistics serve as the "answers" to research questions. These questions are often formally worded as hypotheses (i.e. 'Level of education and violent behavior are significantly related'.) A hypothesis receives scientific support only when a researcher can demonstrate significant empirical evidence, utilizing scientific methods. As you learned in research methods, the best studies are those which utilize entire populations, or consist of larger samples which have been randomly drawn. Statistics are used to summarize large volumes of information, and in doing so, allow research hypotheses to be supported or refuted.

Second, statistics seek to clarify, not confuse, issues. They are a 'language' for communicating results. Even though this language is mathematically based, it is no different, in terms of meaning, than any other language such as English, Japanese, or Greek. Students are often encouraged to approach a class such as quantitative analysis from the perspective of learning a foreign language, not only because this analogy is appropriate, but also because focusing on meaning or outcomes de-emphasizes the computational aspect of statistics that students frequently dread. While mathematical computation is a necessary part of any statistics course, the true goal is to understand what the numbers are 'telling' you. The figures we calculate are making a statement just like a paragraph of text is making a statement.

Different statistics are used in different circumstances just like certain words or phrases are used in different circumstances. Statistics are logical, rational, and complete. There are patterns which are followed and commonalities in meaning. Once we work past any math 'phobias' you may have, learning quantitative analysis is much the same as the process of learning any new language.