SWK5015 t-Test

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Sociology

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Feb 20, 2024

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Brant After-School ACT Prep: t-Test Leah M. Packard LSW/CDCA Capella University SWK 5015: Advanced Research and Statistics in Social Work Dr. Roland 2/11/2024

Brant After-School ACT Prep Program The town of Brant started an after-school program for high school youth to prepare them for the ACT college entrance examination. I have been asked to evaluate the research findings detailed below to determine whether the after-school program had a positive effect on ACT scores. The total sample size was 65 students. Of those 65, 29 participated in the after-school program and 36 did not partake in the program. The mean score on the ACT of the 29 participants who were a part of the after-school program was 24.96. The mean score on the ACT of the 36 students who did not participate in the after-school program was 21.75 (see descriptives table below) Group Descriptives Group N Mean SD SE Coefficient of variation ACT Score Yes 2 9 24.966 3.87 7 0.72 0 0.155 No 3 6 21.750 3.58 9 0.59 8 0.165 In the table below you will find the results of the tests that were run. I utilized the independent sample t-test as this will assist in determining if the after-school program has a positive effect on ACT scores. For this data set, the T-value came out as 3.464. This value indicates the number of standard deviations the sample mean is from the null hypothesis (Navarro et al., 2019). A larger absolute t-value usually means there is a more significant difference between the two (Navarro et al., 2019). In this data set the degrees of freedom rendered 63. The p-value here was .001 which is less than .05, meaning we would reject the null hypothesis, concluding that there is a statistically significant difference between the two groups based on ACT scores. This data suggests that the after-school program was effective in producing higher ACT scores than those students who did not participate.

Independent Samples T-Test t df p ACT Score 3.464 63 < .001 Note. Student's t-test. There are various limitations to consider however when interpreting data or considering a hypothesis. One of the most glaring limitations was that the participants did not take a pre-test to establish a baseline ACT score for each participant. It would also be important to highlight that we do not have adequate information regarding the characteristics of the students that were involved that could have influenced the data such as socioeconomic status, access to other resources et cetera. One other factor that was not accounted for was whether the students who were not in the program participated in any sort of independent study or if they were not permitted to engage in any preparation or study before the exam.

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References Navarro, D.J., Foxcroft, D.R., & Faulkenberry, T.J. (2019). Comparing Two Means. Learning Statistics with JASP: A Tutorial for Psychology Students and Other Beginners. (pp. 1- 43). https://tomfaulkenberry.github.io/JASPbook/chapters/chapter10.pdf

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