This content delves into the practical application of non-parametric tests and relationship exploration in statistical analysis scenarios, specifically focusing on the Statistical Analysis assignment. Three unique situations are explored as part of this assignment, including the impact of the COVID-19 pandemic on political party affiliations, the connection between gender and pet ownership, and the correlation between sports choices and binge-drinking habits among male student-athletes. These case studies provide valuable insights into non-parametric testing and its real-world implications.
Scenario 1: Analyzing Political Party Affiliation Changes During the COVID-19 Pandemic
This assignment aims to assess your ability to conduct non-parametric tests using SPSS and present the results in an organized and clear manner. Non-parametric tests are essential when dealing with nominal data or when data fail to meet the assumptions required for parametric tests. In this scenario, we explore whether there is a significant change in political party affiliations during the COVID-19 pandemic compared to pre-pandemic times in a local precinct.
- Variable of Interest: Party affiliation with three levels: Republican, Democrat, and Others.
- Expected Frequencies:
A chi-square goodness-of-fit test was conducted to assess the similarity between party affiliation during the recent COVID-19 pandemic and pre-pandemic affiliation. The test results indicate that there is no significant difference between the two time periods (x2 (2,N=75) = 1.48, p = .477) Therefore, we conclude that party affiliation during the pandemic remains consistent with the pre-pandemic era. This result suggests that the event of COVID-19 did not influence party affiliation significantly.
0 cells (0.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8.
Scenario 2: Analyzing the Relationship Between Gender and Pet Ownership
This analysis aims to determine whether there is a significant association between an individual's gender and their ownership of pets, including dogs, cats, and reptiles. The results of a chi-square test are presented following the APA format.
- Variables of Interest:
- Gender levels: Male and Female
- Pet ownership with three levels: Dog, Cat, and Reptile
A chi-square test of independence was conducted to examine the association between gender and pet ownership. The results indicate no significant association between gender and pet ownership, as the null hypothesis cannot be rejected (χ^2 (2, N=101) = 3.47, p = .177). This finding suggests that gender does not play a significant role in determining the type of pet individuals own.
The effect size is calculated as
The critical value with alpha of 0.05 and 2 degrees of freedom is 5.991. The obtained value from SPSS output is 3.47. The result showed that the test statistic (3.47) is less than the critical value (5.991) which connotes non-rejection of null hypothesis. therefore, we cannot reject the null hypothesis and this means there is no significant difference.
Scenario 3: Analyzing the Relationship Between Sport and Binge-Drinking Among Male Student-Athletes
This analysis investigates whether the choice of sport is associated with binge-drinking habits among male student-athletes. The data collected from 93 respondents are examined using a chi-square test, and the results are presented following the APA format.
- Variables of Interest:
- Binge drinking with two levels: Yes and No
- Type of sport with three levels: Lacrosse, Hockey, and Swimming
A chi-square test of independence was conducted to determine if there is a significant association between binge-drinking and the type of sport engaged in by male student-athletes. The results indicate that there is no significant association (χ^2 (2, N=93) = 0.272, p = .873). This implies that the type of sport a male student-athlete chooses does not significantly affect their likelihood of engaging in binge-drinking.
The effect size is:
The critical value with alpha of .05 and 2 degrees of freedom is 5.991. The obtained value from SPSS output is 0.27. The result showed that the test statistic (0.27) is less than the critical value (5.991) which connotes non-rejection of null hypothesis. therefore, we cannot reject the null hypothesis and this means there is no significant difference