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This study on the effectiveness of a rehabilitation program for offenders is an example of inferential statistics, as it aims to generalize findings from sample data to a larger population of offenders. Researchers aim to determine if the program influences recidivism rates, which requires drawing conclusions beyond the collected data.

A null hypothesis should be created, assuming the rehabilitation program has no effect on recidivism . This serves as a baseline to test the effectiveness of the program. An alternative hypothesis should also be developed, suggesting that the program reduces recidivism.

For statistical testing, a t-test or ANOVA would be appropriate. A t-test is suitable for comparing recidivism rates between two groups (offenders who participated vs. those who did not). If multiple groups are involved ( different program types), ANOVA would be better.

A chi-square test would not be suitable because it is used for categorical data, while recidivism rates are typically quantitative.

In conclusion, the study requires inferential statistics, with null and alternative hypotheses, and t-test or ANOVA for data analysis.