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RSCH FPX 7864 Assessment 3 t-Test Application and Interpretation

Name

Capella University

RSCH FPX 7864 Quantitative Design and Analysis

Prof. Name

Date

Data Analysis Plan

The plan for data analysis entails investigating how attending review sessions relates to final exam scores. This will be done by conducting a t-test and Levene’s test. The variables under consideration are ‘final’, which measures the number of correct answers on the final exam, and ‘review’, which indicates whether a student attended review sessions (coded as 1 for no attendance and 2 for attendance). Although ‘review’ is treated as a categorical variable, ‘final’ is treated as a continuous variable in this study.

Testing Assumptions

Examining the Equality of Variances (Levene’s Test)
Test
F
df1
df2
p

final

0.740

1

103

0.392

Levene’s test was employed to evaluate whether the variations among the groups were equal. With a p-value of 0.392, the results indicate that there is no notable distinction in variances between students who participated in review sessions and those who did not (Kim, 2015).

Findings & Analysis

T-Test for Unrelated Groups
t
df
p

-0.410

103

0.682

Descriptive statistics for each group:

Group
N
Mean
SD
SE
Coefficient of variation

Participated in the review meeting.

55

61.545

7.356

0.992

0.120

Missed the review session.

50

62.160

7.993

1.130

0.129

RSCH FPX 7864 Assessment 3 t-Test Application and Interpretation

The findings from the t-test indicate that there is no notable distinction in the final exam scores between students who participated in review sessions and those who didn’t (p = 0.682). As a result, there is insufficient evidence to discard the null hypothesis.

Statistical Conclusions

The research findings suggest that there isn’t a notable variance in final exam results between students who participated in review sessions and those who didn’t. Consequently, it seems that attending review sessions doesn’t lead to improved performance in tests.

Application

In areas such as applied behavior analysis (ABA), researchers often employ the independent samples t-test to assess the effectiveness of various therapeutic approaches in addressing behavioral challenges. This statistical tool helps in identifying which interventions are most beneficial for individuals with developmental disabilities.

References

Capella University. (n.d.). 7864 Course Study Guide.

Kim, T. K. (2015). T test as a parametric statistic. Korean Journal of Anesthesiology, 68(6), 540. https://doi.org/10.4097/kjae.2015.68.6.540

RSCH FPX 7864 Assessment 3 t-Test Application and Interpretation



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