PSYC FPX 3700 Assessment 5

Student Name

Capella University

PSYC-FPX3700 Statistics for Psychology

Prof. Name

Date

Assessment 5

Part 1: Categorical Data Analysis

This assessment uses the Assessment_5_Data.csv dataset, representing hypothetical data collected from undergraduate psychology students in a large academic program. Each record represents one student, identified by a unique identification number and categorized based on their admission type and program enrollment.

The variables included are:

Conducting the Chi-Square Test

A chi-square test of independence was conducted using JASP to examine whether there is an association between admit_type and program enrollment. The test determines if the distribution of students across programs varies significantly based on whether they were transfer or first-year students. The analysis included expected frequencies and Cramér’s V as a measure of effect size.

Checking the Assumptions of the Chi-Square Test

To ensure the validity of the chi-square test, two primary assumptions were verified:

1. Independence of Observations:
   Each student appears only once in the dataset and belongs to a single admit_type and program category. This confirms that individual observations are independent.

2. Adequate Expected Cell Counts:
   All expected cell frequencies were greater than or equal to 5, and none were zero. For example:

   Program	First-Year (Expected Count)	Transfer (Expected Count)
   ABA	10.15	18.85
   General Psychology	14.35	26.65
   Pre-Counseling	10.50	19.50

   Since all values met the required threshold, this assumption was satisfied.

Statistical Significance of the Chi-Square Test

At the α = .05 significance level, the chi-square test result was χ²(2, N = 100) = 4.97, p = .084. Since p > .05, the result is not statistically significant. Therefore, the null hypothesis of independence between admission type and program cannot be rejected.

Relationship Between Admit Type and Program

The results indicate no significant relationship between students’ admission type and their program enrollment. Although the relationship was not statistically significant, Cramér’s V = .223, suggesting a small-to-medium effect size. This implies a modest association, even if not strong enough to reach statistical significance.

APA-Style Summary of Results

A chi-square test of independence examined whether the type of admission (first-year vs. transfer) was related to program enrollment (Applied Behavior Analysis, General Psychology, or Pre-Counseling) among 100 students. The test revealed no significant association, χ²(2, N = 100) = 4.97, p = .084, Cramér’s V = .223. Program distributions did not significantly differ by admission type.

Part 2: Analysis of Variance

B) Interpreting a Published Research Article

For this section, the selected article is by Barrett, E., Kannis-Symand, L., Love, S., Ramos-Cejudo, J., & Lovell, G. P. (2023) titled Sports Specific Metacognitions and Competitive State Anxiety in Athletes: A Comparison Between Different Sporting Types published in Applied Cognitive Psychology. The article utilized ANOVA to compare metacognitive beliefs and anxiety levels across various sport types.

Descriptive Statistics

The study reported means (M) and standard deviations (SD) for all outcome variables across four types of sports: endurance, team, individual, and esports. An example of these results is shown below for the MBPQ-PR (Metacognitive Belief in Personal Responsibility) subscale:

These descriptive statistics summarize group differences prior to inferential testing.

Inferential Analyses Conducted

The researchers conducted a series of one-way between-groups ANOVAs, one for each outcome variable. When significant main effects were detected, Bonferroni-adjusted post hoc comparisons were applied to identify specific group differences. Effect sizes were reported using η² (eta squared) to assess the strength of associations.

Type of Analysis of Variance

The analysis involved a one-way between-groups ANOVA. The independent variable was sport type with four levels (endurance, team, individual, and esports). The dependent variables included multiple subscales related to metacognitive beliefs (MBPQ-PW, MBPQ-PA, MBPQ-PR, MBPQ-NC, MBPQ-NT), motivational processes (MPPQ-CC, MPPQ-CE, MPPQ-TC), and competitive state anxiety (CSAI-CA, CSAI-SA, CSAI-SC). No covariates or repeated measures factors were included in this analysis.

Summary of ANOVA Findings

Results showed that certain metacognitive and anxiety-related variables significantly differed by sport type. For example, MBPQ-PR was statistically significant, F(3, N) = 5.76, p = .001, η² = .09, indicating that esports athletes scored highest, whereas endurance and individual athletes scored lower. Additional significant results were found for MBPQ-PA and MBPQ-NC (p = .006; η² = .07). Other variables, such as self-confidence and cognitive anxiety, did not show meaningful differences across groups.

In simpler terms, the study suggests that the type of sport an athlete participates in can influence certain metacognitive beliefs and aspects of anxiety, particularly those involving personal responsibility and awareness of thoughts.

Sample Description and Generalizability

The study included a sample of athletes categorized into four sport types: endurance, team, individual, and esports. Demographic details, including age and gender distribution, were representative of active competitors in each group. These findings can be most appropriately generalized to athletes with similar demographic and competitive characteristics, while caution should be used when extending the results to non-athlete or markedly different athletic populations.

A) Examining a Graduate Program in the Social Sciences

Selected Graduate Program

Master of Arts (M.A.) in Psychological Sciences
Institution: Rutgers University–Camden
Program Link: https://graduateschool.camden.rutgers.edu/psychologicalsciences/

Statistics-Related Admission Requirements

While formal prerequisites are not mandatory, the program recommends prior coursework in statistics and research methodology. Such preparation ensures students possess foundational knowledge for graduate-level quantitative research.

Required Statistics Coursework

Students must complete two core statistics and research courses:

These courses equip students with the analytical tools needed to conduct and interpret psychological research effectively.

Interest in the Program

I would be interested in applying to this program in the future due to its emphasis on empirical research and quantitative skill development. The integration of data analysis, experimental design, and mentorship aligns well with my professional goals of becoming a research assistant and preparing for future doctoral studies in psychology. The program’s structure also encourages hands-on experience with real-world research projects, providing a strong foundation in applied statistics.

References

Barrett, E., Kannis-Symand, L., Love, S., Ramos-Cejudo, J., & Lovell, G. P. (2023). Sports specific metacognitions and competitive state anxiety in athletes: A comparison between different sporting types. Applied Cognitive Psychology, 37(1), 200–211. https://doi.org/10.1002/acp.4040

PSYC FPX 3700 Assessment 5

Rutgers University–Camden. (n.d.). Master of Arts in Psychological Sciences. Retrieved from https://graduateschool.camden.rutgers.edu/psychologicalsciences/