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Data Analysis Plan
This study will explore the impact of gender on a students overall class performance. The variables used are gender : male or female, and the previous grade point average (GPA) . The students gender is mutually exclusive, and cannot be ordered in any meaningful way. Therefore, the variable will have a nominal scale of measurement. Meanwhile, the students previous grade point average (GPA) can be ordered in a meaningful way: from the top student to the last one. Consequently, the variable will have a scale as its measurement level since it has numerical values.
The study will aim to answer one research question: how does gender affect a students GPA in class? The studys null hypothesis will be: gender does not affect a students GPA in class. Meanwhile, an alternate hypothesis will be: that a students gender affects their GPA in the class.
Testing Assumptions
SPSS output for the given assumption
Table 1.0: Independent Samples Test and Levenes test
Assumption Summary
Statistical testing procedures require equal variances in the samples. The Levene test helps in whether several groups used in research have the same variance in the sample population (Wang et al., 2022). From table 1.0, Levenes F= 0.095 and the p=.048. Therefore, do not reject null hypothesis of equal variances since the homogeneity assumption is met. Therefore, the used samples have equal variance and can be statistically tested using the equal variances assumed row.
Results and Interpretation
SPSS output for Main Inferential Statistic(s)
Table 2.0: Groups Statistics
Statistical Results Interpretation
According to the equal variances assumed row in table1.0 Levenes F= 0.095 and the p=.048. In the table we ignore the critical value of t , and use the value of Sig. (2-tailed) as p value. Since 0.048 is d ± (0.05), then we reject the null hypothesis that gender does not affect a students GPA in class.
Statistical Conclusions
Brief Analysis and Conclusions Summary
The study aimed at understanding how gender can affect a students performance in class. The tested data showed that the null hypothesis is rejected since the p < .05. While gender is significant in defining a particular students attributes and experiences in school, it also affect their performance in class.
Analyze the Limitations of the Statistical Test
Although Levenes test help in establishing homogeneity among variables, it has limitations. The test relies too much on the p values that are affected by the sample sizes. The test will have a smaller value for large samples than for small samples with the same variances. Therefore, the test tends to show that samples problems are overstated, and smaller samples problems are understated.
Findings Alternate Explanations and Future Exploration Potential Areas
A students performance in class is affected by various reasons that are not attributed directly to their gender. For instance, students who come from discriminative communities may perform poorly in class due to mental health issues. Therefore, future studies should explore the relationship between mental health and academic performance.
Application
The above analysis is significant in my field of psychology since it helps in identifying potential causes of poor performance among students. The analysis would help me to assume that a particular gender would perform poorer than the other. Therefore, the findings are valuable since I would explore the reasons why one gender performs better than the other. Consequently, I would focus on other issues such as mental health that can potentially lead to poor performance.
References
Wang, Y., Tang, M., Wang, P., Liu, B., & Tian, R. (2022). The Levene test based-leakage assessment. Integration, 87, 182193. Web.
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