wk5Assgn1_Hemphill_L

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Week 5 Assignment1: Simple Logistic Regression LaShurn Hemphill October 1, 2023

I discovered that the mean for Q1(Age) was 37.01 using the Afrobarometer dataset. Creating a study topic that emphasized fostering community cohesion and good social change was my goal. Integrating the communities, we live in and our faith in local law enforcement is the area of social change for which I hope to develop a study question. You may find out the likelihood of something happening or not by utilizing a dichotomous outcome variable, as explained by Walden University (2017j). A binary logistic regression is used to estimate the probability and provide a response to a certain issue, according to the video (Walden University, 2017j). "Does an individual's lived poverty index and trust in government index factors predict the individual's trust in police?" is the study issue I explored. A dichotomous variable, "trust in police," is the dependent variable. Regarding whether a person trusts the police, this is a dichotomous variable with codes of 1 for not at all and 0 for a lot. The person's lived poverty index and their level of faith in the government are the independent variables. The person's lived poverty index and their level of faith in the government are the independent variables. Research Question: Is a person's faith in police predicted by their lived poverty index and government trust index factors? Null Hypothesis: A person's faith in police is not predicted by their lived poverty index or their level of trust in the government. Hypothesis alternative: A person's faith in police is predicted by their lived poverty index and their level of trust in the government. DV: Trust in Police

IV1: Lived Poverty Index IV2: Trust in Government Index The person's lived poverty index and their level of faith in the government are the indepe ndent variables. I might reject the null hypothesis, which states that a person's lived poverty index and faith in the government index predict that person's trust in police, after doing my basic logistic regression in SPSS. The logistic regression's statistical significance (p<.001) allowed me to conclude that it was a well-fitting model. 87.4% of the data concludes that those elements correctly predict police trust, according to the Classification Table, that is used to display the responses to the model predictions. The person's lived poverty index and their level of faith in the government are the indepe ndent variables. According to the Hosmer Lemeshow Test, the model fits well since the statistical significance is p<.001. Upon examining the parameters in the formula table, I concluded that although the lived poverty index (B= -.020) does not show a significant correlation with police trust, the government trust index (B=.631) does show a significant correlation, indicating that the higher the government trust index, the greater the overall level of police trust. There is a higher chance that the variables will predict one another when the B value is positive. Finally, I concluded that the null hypothesis, according to which the lived poverty index and government trust are predictors of police trust, could be rejected. This is a subject that needs greater investigation since ensuring that the public has faith in the police will merely make it more likely that people will be cooperative, build rapport, and become more like one another in general. Communities can more easily work toward fostering positive social change if they have greater faith in the police and positive community policing.

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