CRJ_575_Module_5_Discussion

Research studies have found that race is a consistent predictor of attitudes toward the police. Some researchers suggest that people’s experience during police stops can be an important reason for their attitudes toward police. Questions have been raised about bias in the decision to initiate a stop and in other aspects of the traffic stop: the length of the stop and the decision to cite, search, or use force. This discussion provides an opportunity for you to explore, with the data set 32022 PoliceContactSurvey.sav Download 32022 PoliceContactSurvey.sav , whether the experience with police during a traffic stop differs significantly between white and black respondents by using the methods you’ve learned in Module 5. Race will be treated as the independent variable in this exercise.  First, examine the measurement (categories) of race in the data file.  Second, examine the meaning and measurement of the following variables: V8, V9, V10, V6A, V6B, 12B, V6E, 6H, V47, V6G, V8A5, V8A1, or some other variables of your interest.  Select two dependent variables and perform crosstabs; select statistics which include Chi- Square, Lambda, and Cramer’s V for analysis.  Before performing statistics, you need to take the following steps to ensure that this analysis will only include the information of the respondents who clearly identified themselves as black or white. a. In the editing bar, click “Data”. b. In the dropdown box, select “Select Cases,” toward the bottom of the box. c. In the box of Select Cases, check “If condition is satisfied” and check the choice “if”. d. In the “if” box, type “Race=1 or Race=2,” click “Continue”. e. Click “OK”. With this procedure, you tell SPSS that your following analysis will only include the cases in which the respondent clearly identified him/herself as white (1) or black (2).  In your initial post, 1) state your hypotheses and null hypotheses, 2) state the meaning of each dependent variable you select, and 3) state the findings with the properly numbered tables and conclusions in reference to the null hypotheses. Note : The expected counts in each cell must be 5 or greater. If this rule is violated in a table, you should consider changing the dependent variable and try another instead. In your initial post, 1) state your hypotheses and null hypotheses, 2) state the meaning of each dependent variable you select, and 3) state the findings with the properly numbered tables and conclusions in reference to the null hypotheses. What would I state for my hypotheses and null hypotheses, state the meaning of each dependent variable (Police shouted at respondent, and police cursed at respondent), and state the findings with the properly numbered tables and conclusions in reference to the null hypotheses.

Discussion 5 Formulated I just want to say upfront that in all honesty, I had such a difficult time with this exercise. I’m not sure what or where I went wrong. I became so flustered that I’m not sure what steps I took in the end to get any data. Things just seem to go wrong when taking the steps to ensure that this analysis only includes the information of the respondents who clearly identified as black or white. Dr. Koehle, I followed the instructions exactly but upon glancing at the output once that statistics were run, nowhere did I see anything to do with race. So, I repeated everything several times and still experienced the same problem. Eventually, I just tried a different way and even though I know it can’t possibly be the correct way, I am posting this because I did try….many, many times. Please, if anyone could possibly point out or see where I went wrong or explain to me from beginning to end the correct way to perform the steps, I’d appreciate it. Thank you. Hypotheses: Null Hypothesis (HO) – There is no significant association between whether the police shouted at the respondent and whether the police cursed at the respondent among individuals who identified themselves as Black only or White only. Alternative Hypothesis (H1) – There is a significant association between whether the police shouted at the respondent and whether the police cursed at the respondent among individuals who identified themselves as Black only or White only. Meaning of Dependent Variables: V6A Police Shouted At Respondent (Dependent variable 1) – This variable indicates whether the police shouted at the respondent during a specific incident or encounter. It is a categorical variable with two levels which are Yes or No. In the context of my analysis, it represents whether the respondent experienced shouting, such as verbal aggression, from the police. V6B Police Cursed at Respondent (Dependent variable 2) – Indicates whether the police used offensive language or cursed at the respondent during a specific incident or encounter. This too is a categorical variable with two levels being Yes or No. It represents whether the respondent experienced verbal abuse, or cursing, from the police. Findings and Conclusions: Table 1: Crosstabulation of Police Shouted at Respondent and Police Cursed at Respondent POLICE CURSED AT RESPONDENT Yes No Total POLICE SHOUTED AT RESPONDENT Yes 39 45 84 No 3 28 31 Total 42 73 115 Table 2: Chi-Square Tests Pearson Chi-Square: χ² = 13.192, df = 1, p < .001

Missing 67887 67888 0 Frequency Table POLICE SHOUTED AT RESPONDENT Frequenc y Percent Valid Percent Cumulative Percent Valid Yes 85 .1 73.3 73.3 No 31 .0 26.7 100.0 Total 116 .2 100.0 Missing Out of universe/missing 67887 99.8 Total 68003 100.0 POLICE CURSED AT RESPONDENT Frequenc y Percent Valid Percent Cumulative Percent Valid Yes 42 .1 36.5 36.5 No 73 .1 63.5 100.0 Total 115 .2 100.0 Missing Out of universe/missing 67887 99.8 Do not know 1 .0 Total 67888 99.8 Total 68003 100.0 RACE OF RESPONDENT Frequenc y Percent Valid Percent Cumulative Percent Valid White only 60204 88.5 88.5 88.5 Black only 7799 11.5 11.5 100.0 Total 68003 100.0 100.0

Crosstabs Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent POLICE SHOUTED AT RESPONDENT * POLICE CURSED AT RESPONDENT 115 0.2% 67888 99.8% 68003 100.0% POLICE SHOUTED AT RESPONDENT * POLICE CURSED AT RESPONDENT Crosstabulation Count POLICE CURSED AT RESPONDENT Total Yes No POLICE SHOUTED AT RESPONDENT Yes 39 45 84 No 3 28 31 Total 42 73 115 Chi-Square Tests Value df Asymptotic Significance (2-sided) Exact Sig. (2- sided) Exact Sig. (1- sided) Pearson Chi-Square 13.192 a 1 <.001 Continuity Correction b 11.654 1 <.001 Likelihood Ratio 15.231 1 <.001 Fisher's Exact Test <.001 <.001 Linear-by-Linear Association 13.077 1 <.001 N of Valid Cases 115 a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 11.32.

Approxi mate Signific ance Nominal by Nominal Lambda Symmetric . b POLICE SHOUTED AT RESPONDENT Dependent . b POLICE CURSED AT RESPONDENT Dependent . b Goodman and Kruskal tau POLICE SHOUTED AT RESPONDENT Dependent <.001 c POLICE CURSED AT RESPONDENT Dependent <.001 c a. Not assuming the null hypothesis. b. Cannot be computed because the asymptotic standard error equals zero. c. Based on chi-square approximation Symmetric Measures Value Approximate Significance Nominal by Nominal Phi .339 <.001 Cramer's V .339 <.001 N of Valid Cases 115