PSYC FPX 4600 Assessment 3 Data Analysis and Interpretation
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PSYC FPX 4600 Assessment 3 Data Analysis and Interpretation

PSYC FPX 4600 Assessment 3 Data Analysis and Interpretation

Name

Capella University

PSYC FPX 4600 Research Methods in Psychology

Prof. Name

Date

Data Analysis and Interpretation

In the data analysis and interpretation section, statistical or numerical methods are employed to test the data. For this research, the ANOVA single-factor test will be utilized to analyze and interpret the data for hypothesis results. The analysis will adhere to statistical APA style, which is widely used for reporting research findings (Kyonka et al., 2019).

Interpretation of Statistical Findings

According to the statistical findings derived from the ANOVA results, ethnicity among communities or students does not significantly impact grades and educational performance (Hoijtink et al., 2019). Neither students nor professors perceive any differences among students based on cultural background, gender, color, or race. This study paves the way for future researchers to explore other discriminatory factors and assess their effects on students’ academic records. The provided table illustrates the statistical findings concerning independent and dependent variables.

ANOVA:

SOURCE OF VARIATION     SS      df      MS          F             P-Value       F-crit
BETWEEN GROUPS          132.2473  16     8.265458    7.250311      3.15E-15      1.664263
WITHIN GROUPS           556.3269  488    1.140014                                      
TOTAL                   688.5743  504

PSYC FPX 4600 Assessment 3 Data Analysis and Interpretation

The one-way ANOVA indicates that the impact of ethnicity on students’ grades is negligible, with p = 3.15. A statistical significance of 688.5 is found, refuting the hypothesis. The ANOVA single-factor test is applied to obtain mean values of the data and to calculate variance, determining the similarity between dependent and independent variables. ANOVA yields p-values greater than 0.05, indicating dominance of the null hypothesis. The obtained p-value of 3.15 is significantly higher than 0.05, suggesting that ethnicity has no significant impact on grades and academic performance. Most respondents consider ethnicity a secondary factor affecting students’ grades and educational performance. Additionally, the high value for degrees of freedom (df) of the Single ANOVA test refutes the hypothesis. Results from ANOVA suggest that factors such as personal abilities, family values, and financial status may significantly influence students’ grades and academic performance, highlighting the educational sector’s progress in overcoming racial discrimination.

Demographic Statistics

For statistical analysis, it is necessary to consider demographic factors such as race, age, and gender (Petritis & PhD, 2018). Demographic results may vary due to socioeconomic factors such as education and social status (Mishra et al., 2019). In the statistical analysis using ANOVA single factor, demographic questions are included to ascertain respondents’ qualifications, gender, work experience, and age. Respondents aged 15-55 are included in the study with a 10-year scale. Thirty responses are collected to obtain real-time data for the hypothesis. Google Forms is utilized to collect data, and the responses are recorded in Excel. Consequently, the results confirm that ethnicity among communities or students has no significant impact on grades and educational performance (Hoijtink et al., 2019).

References

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. https://doi.org/10.1037/met0000201

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. https://doi.org/10.1002/jeab.509

PSYC FPX 4600 Assessment 3 Data Analysis and Interpretation

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. https://doi.org/10.4103/aca.aca_94_19

Petritis, B., & PhD. (2018, November 20). t-test & ANOVA (Analysis of Variance). RayBiotech.comhttps://www.raybiotech.com/learning-center/t-test-anova/