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Feb 20, 2024
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Evaluating the Significance of Findings
LaTasha Sherie Ponder
Doctor of Philosophy in Criminal Justice, Walden University
CRJS-8210 J-1: Quantitative Reasoning and Analysis
Dr. Dan David Jones
September 30, 2023
Week 5 assignment
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Evaluating the Significance of Findings
Scenario.1
Sample Size:
The sample size in this study consists of 65 students in face-to-face classes and 69 students in online classes, for a total sample size of 134. While not overly large, it is reasonable for an exploratory study and provides a decent sample to draw initial insights. However, the impact of sample size on statistical significance should still be considered (Frankfort-Nachmias & Guerrero, 2021).
Statistical Significance:
The independent samples t-test resulted in a t-value of 1.8 and a p-value of 0.74. The p-value does not indicate statistical significance at conventional thresholds (typically p<0.05). Instead, it is described as "rapidly approaching significance." A p-value of 0.06 alone is not conclusive evidence to support statistically significant findings. It's important to interpret it with caution and
consider the effect size and the overall research context (Greenland et al., 2016).
Meaningfulness of Statements:
The statement reports that students in online quantitative reasoning classes have higher levels of satisfaction than those in face-to-face classes based on the observed mean values (M) of 3.89 and
3.39, respectively. However, this conclusion is not well-supported by the statistical analysis because the p-value does not reach statistical significance.
Implications for Social Change:
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Based on the information provided, it is not appropriate to draw immediate implications for social change because the findings lack statistical significance. Further research with a larger sample size may be needed to provide more robust before advocating any specific changes in educational practices.
Scenario .2
Sample Size:
The sample size in this study includes 36 European Americans, 23 African Americans, and 18 Hispanics, totaling 77 participants. The sample sizes for each racial group are relatively small. While it's not uncommon to have varying sample sizes across groups in social science research, it is important to consider whether these sample sizes are sufficient to detect meaningful differences.
Statistical Significance:
The one-way analysis of variance (ANOVA) resulted in an F-value of 1.789 and a p-value of 0.175. The p-value of 0.175 suggests that the observed differences in educational attainment across the three races are not statistically significant at conventional thresholds (typically p<0.05). Therefore, we cannot conclude that there are differences in educational attainment based on this analysis.
Meaningfulness of Statements:
The statements claim reports that the results shed light on the current social conversation about inequality. However, because the ANOVA does not show statistically significant
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differences in educational attainment across the three races, these results cannot directly address the topic of inequality in education. Further research and analysis would be needed to understand
the complexities of educational disparities and the role of race in contributing to them.
Implications for Social Change:
The results suggest that educational attainment may not differ significantly based on race, but
further investigation should be conducted with larger sample sizes and more robust research designs to provide stronger evidence and support any specific implications for social change.
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References
Frankfort-Nachmias, C. & Leon-Guerrero, A. (2021). Social statistics for a diverse society. (9
th
ed).
Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016). Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations.
European Journal of Epidemiology
,
31
(4), 337–
350.
http://www.jstor.org/stable/44851769
.