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PSYC FPX 4600 Assessment 3 Data Analysis and Interpretation


Capella University

PSYC FPX 4600 Research Methods in Psychology

Prof. Name


Data Analysis and Interpretation

In this section, statistical methods are employed to examine the data. This research utilizes the ANOVA single-factor test to analyze and interpret data for hypothesis testing. The analysis follows the statistical APA style, which is widely accepted for reporting research findings (Kyonka et al., 2019).

Interpretation of Statistical Findings

The statistical findings from the ANOVA results indicate that ethnicity among communities or students does not significantly impact grades and educational performance (Hoijtink et al., 2019). Neither students nor professors perceive differences among students based on cultural background, gender, color, or race. This study encourages future researchers to investigate other discriminatory factors and their effects on students’ academic records. The table below presents the statistical findings related to independent and dependent variables.

ANOVA Results

Source of Variation
Between Groups132.2473168.2654587.2503113.15E-151.664263
Within Groups556.32694881.140014   

PSYC FPX 4600 Assessment 3 Data Analysis and Interpretation

The one-way ANOVA results indicate that the impact of ethnicity on students’ grades is minimal, with p = 3.15. The statistical significance found is 688.5, which refutes the hypothesis. The ANOVA single-factor test calculates the mean values of the data and variance, showing the similarity between dependent and independent variables. The p-values obtained are greater than 0.05, indicating the dominance of the null hypothesis. The p-value of 3.15, being significantly higher than 0.05, suggests that ethnicity does not significantly impact grades and academic performance. Most respondents consider ethnicity a secondary factor affecting students’ grades and educational performance. Moreover, the high degrees of freedom (df) in the Single ANOVA test further refutes the hypothesis. The results suggest that personal abilities, family values, and financial status may significantly influence students’ grades and academic performance, highlighting progress in the educational sector in overcoming racial discrimination.

Demographic Statistics

For statistical analysis, it is essential to consider demographic factors such as race, age, and gender (Petritis & PhD, 2018). Demographic results can vary due to socioeconomic factors such as education and social status (Mishra et al., 2019). In this study, demographic questions are included in the ANOVA single-factor analysis to ascertain respondents’ qualifications, gender, work experience, and age. Respondents aged 15-55 are included, using a 10-year scale. Thirty responses are collected to provide real-time data for hypothesis testing. Data collection is conducted via Google Forms, with responses recorded in Excel. The results confirm that ethnicity among communities or students does not significantly impact grades and educational performance (Hoijtink et al., 2019).


Hoijtink, H., Mulder, J., van Lissa, C., & Gu, X. (2019). A tutorial on testing hypotheses using the Bayes factor. Psychological Methods, 24(5), 539–556.

Kyonka, E. G. E., Mitchell, S. H., & Bizo, L. A. (2019). Beyond inference by eye: Statistical and graphing practices in JEAB, 1992-2017. Journal of the Experimental Analysis of Behavior, 111(2), 155–165.

Mishra, P., Singh, U., Pandey, C., Mishra, P., & Pandey, G. (2019). Application of student’s t-test, analysis of variance, and covariance. Annals of Cardiac Anaesthesia, 22(4), 407.

PSYC FPX 4600 Assessment 3 Data Analysis and Interpretation

Petritis, B., & PhD. (2018, November 20). t-test & ANOVA (Analysis of Variance). RayBiotech.com

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