100 word response 1 reference/intext citation
Due 5/2/2025
Martin
The distinction between descriptive and inferential statistics, as I mentioned in my previous assignment evaluating the Crisis Intervention Team program through the Greenville Police Department, is important to understanding which statistics you will be using to analyze your program’s data. Descriptive statistics summarize and organize data to obtain a better understanding of the data at hand. Some of the descriptive statistics that could be calculated in the CIT program include the average number of arrests before and after the training, the percentage of referrals to mental health services, etc. or the demographic breakdowns of people who encountered mental health crises. Immediate and accessible information on trends in arrest and referral rates or officer participation levels can be provided by these statistics (Vito & Higgins, 2015). For example, inferential statistics help make predictions or generalizations about the population based on the sample. For instance, we use a paired t-test to compare pre- and post-training survey results to determine if observed knowledge or confidence improvements are statistically significant above chance. The statistical inference presented in this form of inference proves that CIT training is effective beyond description (Davoust et al., 2021). Several statistical tools are suitable for conceptualizing and analysis of the CIT program data. Patterns in arrest or referral rates over time can be asked to identify. By crossing tabulation, the relationships between variables like the type of mental health crisis and intervention outcomes could be explored.
Furthermore, logic models (part of your evaluation framework) visually represent the relationships between program input, activities and outcomes to help stakeholders understand how these statistical discoveries fit with planned results (Vito & Higgins, 2015). In short, the evaluation of the CIT program is based on both descriptive and inferential statistics. Descriptive statistics offer snapshots of performance, while inferential statistics support data-driven decision-making and generalizability of findings.
