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Pages:
2 pages/≈550 words
Sources:
4 Sources
Level:
MLA
Subject:
Accounting, Finance, SPSS
Type:
Coursework
Language:
English (U.S.)
Document:
MS Word
Date:
Total cost:
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Topic:

Statistics (Coursework Sample)

Instructions:
This coursework paper explores the application of Statistical Package for Social Sciences (SPSS) software in analyzing inferential statistics and conducting hypothesis tests. The study aims to provide a comprehensive understanding of the process of data analysis, hypothesis formulation, and statistical testing using real-world data. source..
Content:
Student Name Institution Affiliation Course Professor Date Analysis of Police Officers Chi-square test The chi-square test was conducted at a 95% confidence interval and 0.05 alpha level to find out whether there a significant association between police officer’s gender and military experience. Therefore, the null hypothesis indicated no association between gender and military experience while research hypothesis indicated a significant association between gender and military experience (Whatley et al., 57). The Pearson chi-square was 2.248 and the P-value was 0.134. The P-value was above 0.05 significance level implying that we failed to reject the null hypothesis and affirmed no significant association between police officer’s gender and military experience. Paired t-test The test was conducted at a significance level of 0.05 to find out whether there was a significant mean difference between police officer’s age across different race groups. The analysis t-statistic was 22.298, and the P-value was 0.0001. The P-value was below 0.05 alpha level signifying that there was a significant mean difference of police officers ages across different race groups (Gerald et al., 50). Therefore, police officers age differed for each race group. Independent t-test An independent t-test was conducted at a 95% confidence interval and 0.05 alpha level to find out whether there was a significant mean difference of police officer’s age based on gender. Thus, the null hypothesis implied equal mean of officer’s age across gender groups while the research hypothesis stated that police officers ages were not equal across different gander groups. The statistics in the table above indicates that the t-statistic was 0.746 and the P-value was 0.982. The P-value was above 0.05 alpha level implying that we failed to reject the null hypothesis of the study. Therefore, there was no significant mean difference of police officer’s ages across different gender groups. Hence, there was no significant age difference of police officers based on gender (Gerald et al., 50). One-way ANOVA test The test was conducted at a significance level of 0.05 to find out whether there was a significant mean difference of police officers law enforcement experience (post academy) based on education (Gerald et al., 50). The null hypothesis implied that law enforcement experience was equal across all education groups while the research hypothesis implied that at least one education group law enforcement experience differed. The analysis indicated no significant mean difference of police officers law enforcement experience (post academy) based on education (F-statistic = 1.177, P = 0.331). The ANOVA test ascertains that police officers had approximately equal law enforcement experience (post academy) based on education attainment (Leech et al., 355). Regression analysis The analysis was conducted at a 0.05 alpha level to find out whether there was a significant linear association between police officer’s age and law enforcement experience (post academy). The response variable was law enforcement experience while police officer’s age was the predictor variable (...
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