PSYC FPX 3700 Assessment 1

PSYC FPX 3700 Assessment 1

Student Name

Capella University

PSYC-FPX3700 Statistics for Psychology

Prof. Name:

Date

Assessment 1 Part 1: Introduction to Statistics in Psychology

A) Introduction to Research Methods

The present assessment explores a dataset obtained from the General Social Survey (GSS), a large-scale research initiative designed to collect comprehensive social and behavioral data from a representative sample of adults in the United States. The GSS gathers information on diverse variables that reflect demographic, social, and psychological dimensions. In this particular analysis, the focus is placed on two variables: Race and Mental Health (Mntlhth).

• Race: Categorized into three groups — Black, White, and Other.

• Mntlhth: Represents the number of days within the past 30 days during which an individual experienced poor mental health.

The objective of this analysis is to investigate whether there are statistically significant differences in the average number of days individuals from different racial backgrounds experience poor mental health.

Question 1: To which population can the findings be generalized if differences are found among racial groups?

If a researcher determines that the average number of days with poor mental health differs among racial groups using the GSS data, these findings can be generalized to the adult population of the United States. This generalization is appropriate because the GSS employs a nationally representative sampling strategy that captures diverse demographic characteristics across regions, genders, socioeconomic statuses, and cultural groups. Consequently, the results reflect the experiences of American adults rather than any specific subgroup or localized population.

Question 2: Can the researcher conclude that race caused these differences? Why or why not?

No, the researcher cannot conclude that race caused these differences in mental health. The GSS is a correlational and observational survey, not an experimental design. As such, it identifies associations rather than causal relationships. Numerous confounding variables—such as income level, access to healthcare, education, and exposure to discrimination—may mediate or moderate the relationship between race and mental health outcomes. Without experimental manipulation or control over these extraneous factors, causality cannot be inferred (Gravetter & Forzano, 2021).

Question 3: How might the limited racial categories affect the study’s validity?

The restriction of racial categories to “Black,” “White,” and “Other” poses a threat to the study’s construct validity. This classification oversimplifies the rich racial and ethnic diversity present in the United States, leading to potential misrepresentation and loss of nuanced data. For instance, individuals identifying as Asian, Hispanic, Indigenous, or multiracial are aggregated into the “Other” category, obscuring within-group variability. Consequently, this limitation reduces the interpretive accuracy of the study and may result in biased or incomplete conclusions regarding racial disparities in mental health (Sue et al., 2019).

B) Exploring Post-Graduation Opportunities

This section examines opportunities related to psychology that incorporate statistical methods. The student may select either a graduate program (Option A) or a job posting (Option B) that requires statistical proficiency.

Option A: Graduate Program in Psychology and Statistics

Program Name:
Master of Science in Quantitative Psychology

Institution and Link:
Indiana University Bloomington – https://psych.indiana.edu/graduate/quantitative/

Statistics-Related Entrance Requirements:
Applicants must demonstrate strong quantitative skills through prior coursework in statistics or research methods. A minimum of one undergraduate course in inferential statistics is required, and familiarity with software such as R, JASP, or SPSS is considered advantageous.

Statistics Courses Required in the Program:
The curriculum includes the following core courses:

Course Title	Description
PSY-P553: Advanced Statistical Techniques	Covers regression, ANOVA, and multivariate methods.
PSY-P554: Structural Equation Modeling	Focuses on modeling latent variables and path analysis.
PSY-P657: Measurement Theory	Explores psychometrics, test reliability, and validity.
PSY-P558: Data Analysis Using R	Provides hands-on training in data coding, cleaning, and visualization in R.

This program prepares students for research and academic careers that demand advanced knowledge in data interpretation and quantitative analysis within psychological contexts.

Part 2: Introduction to Statistics in Psychology

A) Getting Started with JASP

To complete this section, access to the JASP Statistical Software is required. JASP is a free, open-source program designed for both descriptive and inferential statistical analysis. The dataset utilized, GSS_30s.csv, is a subset of the GSS dataset containing responses from adults aged 30–39 who participated in the 2022 survey.

Variables Included in the Dataset:

Variable Name	Measurement Level	Description
year	Interval	Year of data collection
id_	Nominal	Unique participant ID
childs	Ratio	Number of children reported
age	Ratio	Participant’s age in years
sex	Nominal	Sex assigned at birth (“Male,” “Female”)
race	Nominal	Race category (“Black,” “White,” “Other”)
income	Ordinal	Income range in predefined brackets
mntlhlth	Ratio	Number of days with poor mental health in the past month
depress	Nominal	Whether the participant has been diagnosed with depression (“Yes,” “No”)

Students are instructed to:

1. Download the dataset from Canvas.

2. Open JASP and import the file.

3. Adjust variable types appropriately.

4. Capture a screenshot of the dataset showing variable types for documentation.

(Insert screenshot of the JASP worksheet showing variable types here.)

B) Computing Descriptive Statistics in JASP

Using the GSS_30s.csv dataset, descriptive statistics for the Mntlhth variable were computed using JASP. The analysis included the sample size (N), mean, median, standard deviation (SD), variance, and quartiles (Q1 and Q3).

(Insert screenshot of JASP descriptive statistics table here.)

Summary of Descriptive Statistics for Mntlhth

Based on the results, the mean number of days of poor mental health reported within the last 30 days was M = 5.73, with a standard deviation of SD = 8.91, across a sample of N = 450 participants. These findings indicate moderate variability in mental health experiences among respondents, suggesting that while most participants reported few poor mental health days, some individuals experienced substantially more.

Descriptive Statistics by Race

The Mntlhth variable was further analyzed by race to explore group differences.

(Insert screenshot of JASP descriptive statistics by race table here.)

Race	N	Mean (M)	Median	SD	Variance	Q1	Q3
Black	120	6.80	4.00	9.30	86.49	1.00	9.00
White	250	5.10	3.00	8.50	72.25	0.00	7.00
Other	80	5.90	4.00	9.00	81.00	1.00	8.00

Summary of Findings

Across racial groups, differences were observed in the average number of days participants experienced poor mental health. Black respondents reported the highest mean (M = 6.80), followed by those identifying as “Other” (M = 5.90) and White respondents (M = 5.10). While the observed pattern suggests disparities, further inferential testing (e.g., ANOVA) would be required to determine whether these differences are statistically significant.

References

Gravetter, F. J., & Forzano, L. B. (2021). Research methods for the behavioral sciences (6th ed.). Cengage Learning.

Sue, D. W., Sue, D., Neville, H. A., & Smith, L. (2019). Counseling the culturally diverse: Theory and practice (8th ed.). John Wiley & Sons.

General Social Survey (GSS). (2022). General Social Survey: 2022 Cross-section. NORC at the University of Chicago. https://gss.norc.org/

PSYC FPX 3700 Assessment 1

Indiana University Bloomington. (2025). Master of Science in Quantitative Psychology. Department of Psychological and Brain Sciences. https://psych.indiana.edu/graduate/quantitative/

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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