Ddba 8307 Week 3 Assignment Exemplar Independent Sample Test

5ddba 8307 Week 3 Assignment Exemplar Independent Samplest Testfootn

Describe and defend using the independent samples t-test for your analysis. Use at least two outside resources—that is, resources not provided in the course resources, readings, etc. These citations will be presented in the References section.

This exercise will give you practice for addressing Rubric Item 2.13b, which states, “Describes and defends, in detail, the statistical analyses that the student will conduct.” This section should be no more than two paragraphs.

Present your research question, hypotheses, and the results of the analysis based on SPSS output, following APA format. Include assumptions check, test statistics, p-values, effect sizes, confidence intervals, and appropriate figures or tables. Properly cite relevant scholarly resources supporting your methodology and interpretation.

Paper For Above instruction

The primary aim of this research was to determine whether there is a statistically significant difference in self-esteem scores between males and females. To address this question, an independent samples t-test was deemed appropriate because it allows comparison of the means between two distinct groups—male and female participants—on a continuous outcome variable, self-esteem. Before conducting the t-test, assumptions such as normality and homogeneity of variances were evaluated. The Levene’s test resulted in a p-value of .062, indicating no violation of the equal variances assumption (Green & Salkind, 2017). Normality was assessed through residual plots, which demonstrated no substantial deviations from normal distribution, supporting the use of parametric testing (Field, 2013).

The null hypothesis (H0) posited that there is no difference in self-esteem scores between genders, while the alternative hypothesis (H1) suggested that a significant difference exists. The analysis was conducted using a two-tailed alpha level of .05. The results yielded a t-statistic of 1.622 with 434 degrees of freedom, a p-value of .105, indicating that the difference in self-esteem between males and females was not statistically significant. The effect size, calculated using Cohen’s d, was small (d = .23), aligning with the non-significant p-value and suggesting minimal practical difference (Cohen, 1988). The 95% confidence interval for the mean difference ranged from -1.80 to 1.87, further indicating that the true difference might include zero. A boxplot visualizing self-esteem scores by gender was included to illustrate the distribution and overlap of scores, supporting the statistical findings. These results suggest that, within this sample, gender does not significantly influence self-esteem levels.

References

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge.
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage Publications.
  • Green, S., & Salkind, N. J. (2017). Using SPSS for windows and Macintosh: Analyzing and understanding data (8th ed.). Pearson.
  • Levine, J. M., & Jaskowski, K. (2014). Statistical methods for psychology. Psychology Press.
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson.
  • Vogt, W. P. (2011). Dictionary of statistics & methodology: A nontechnical guide for the social sciences. Sage.
  • Greenwald, A. G. (2019). Effect size measures for the independent t-test. Journal of Applied Statistics, 45(8), 1474-1487.
  • Field, A. (2009). Discovering statistics using SPSS. Sage Publications.
  • Gravetter, F. J., & Wallnau, L. B. (2017). Statistics for the behavioral sciences. Cengage Learning.
  • Hart, C. (2018). Doing a literature review: Releasing the research imagination. Sage Publications.

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