Submit a 1page paper analyzing the relationship between study design and statistical analysis used in the case study.

• Explain why you think that the agency created a plan to evaluate the program.
• Explain why the social work agency chose to use a chi-square statistic to evaluate whether there is a difference between those who participated in the program and those who did not. (Hint: Think about the level of measurement of the variables.)
• Describe the research design in terms of observations (O) and interventions (X) for each group.
• Interpret the chi-square output data and provide support for your interpretation. (Hint: Review the value.) What do the data say about the program?

Use the Learning Resources to support your paper. Make sure to include appropriate APAcitations and a reference list.

below i have the assignment completed but i just need it in my own works so i wont get in trouble for copying, please help me.

Purpose of the Evaluation

Agency probably established a plan to evaluate the success of its program. This plan of evaluation determines if there is any difference noticed found among those who have attended the program and those that haven't. This way, the agency can make its data-driven decisions towards the continuation, modification, or termination of the program. Evaluating the outcomes through a statistical approach such as the chi-square also ensures that the conclusion is based on empirical evidence rather than assumptios and anecdotes (Dudley, 2020).

Choice of Chi-Square Statistic

Since the variables in question were of categorical types-participation in a program, as categorized as yes/no, and an outcome variable that reflects the impact of the program, such as change in behavior or another dichotomous outcome-the chi-square test was used. Chi-square tests are used on outcomes in which relative frequencies are compared between groups. It can therefore be used here to determine whether the distribution of program outcomes is drastically different from one group, that is, participants and non-participants. According to Flannelly, Flannelly, & Jankowski, this is an appropriate method for evaluating the independence of two categorical variables when the data are nominal or ordinal.

Research Design

Research design in this study would be explained through observations O and interventions X. The divide for the groups can be into participants and non-participants of the program. To conduct the experiment, participants X will receive an intervention-assumed to be some sort of social work service-and non-participants no intervention will serve as the controlgroup. Observations (O) will be taken subsequent to the intervention and used to assess the outcome of both groups.

Group 1 (Program Participants): O1 (pre-intervention observation) X (intervention) O2 (post-intervention observation)

Group 2 (Non-participants): O1 (pre-observation) O2 (post-observation without intervention)

Interpretation of Chi-Square Output

The chi-square output will be useful in deciding whether the observed difference between groups is statistically significant. We can compare the calculated value of the chi-square statistic with the critical value of the same for a given degree of freedom to potentially reject the null hypothesis, where the calculated value of the chi-square statistic is greater than the critical value. Alternatively, we might say that an association between program participation and outcomes exists if we can actually reject the null hypothesis. For instance, if the p-value is less than 0.05, it means the participation in the program had a measurable effect on the outcome. This implies if the program is non-significant, then it has failed to produce meaningful differences between participants and non-participants. In this finding, an agency can make a decision on whether the program is effective or not (Dudley, 2020).

Conclusion

This case study's research design and that statistical analysis suited the evaluation of a social work intervention. Through the application of the chi-square statistic, the agency was able to determine whether differences in outcome distribution between participants and non-participants were considered considerable enough, and also gave much insight into the impact of the program.

References

Dudley, J. R. (2020). Social work evaluation: Enhancing what we do (3rd ed.). Oxford University Press.

Flannelly, K. J., Flannelly, L. T., & Jankowski, K. R. B. (2018). Threats to the internal validity of experimental and quasi-experimental research in healthcare. Journal of Health Care Chaplaincy, 24(3), 107-130.https://doi.org/10.1080/08854726.2017.1421019