PSYC FPX 3700 Assessment 2

Student Name

Capella University

PSYC-FPX3700 Statistics for Psychology

Prof. Name

Date

Assessment 2 Part 1: Data Visualization

Dataset Overview

For this assessment, the dataset GSS_30s.csv (available on the Week 3 Assessment page in Canvas) was analyzed. The data were drawn from the General Social Survey (GSS) and restricted to individuals between the ages of 30 and 39 who participated in 2022. Although further exploration of the GSS is optional, detailed information about the survey and its methodology can be found on the official GSS website.

The dataset contains a range of demographic and mental health-related variables that offer valuable insights into participants’ well-being and social characteristics. The variables are outlined in Table 1.

Table 1

Description of Variables in GSS_30s.csv

Variable Name	Description
year	The year in which the participant’s data were collected
id_	A unique identification number assigned to each participant
childs	The number of children the participant has
age	Participant’s age in years
sex	Sex assigned at birth (Male or Female)
race	Self-reported race (Black, White, or Other)
income	Annual income category or range
mntlhlth	Number of days with poor mental health in the last 30 days
depress	Whether the participant has ever been told by a professional that they have depression (Yes or No)

A) Univariate Graph

Graph Construction

A histogram of the mntlhlth (mental health days) variable was constructed using JASP to visually represent the distribution of poor mental health days reported by participants.

Interpretation for a Non-Statistical Audience

The histogram illustrates that most individuals in the 30–39 age range reported few or no poor mental health days in the past month. The data show a right-skewed distribution, meaning that while most respondents experienced few days of poor mental health, a smaller number reported significantly more frequent mental health challenges. This pattern implies that the majority of participants maintain stable mental well-being, but a subset of the population experiences substantial psychological distress over a typical 30-day period. Such findings align with general population trends showing variability in self-reported mental wellness among adults (Smith et al., 2022).

B) Bivariate Graph

Graph Construction

A raincloud plot was generated in JASP to compare participants who reported having a professional diagnosis of depression versus those who did not. The dependent variable was mntlhlth (poor mental health days), while depress (depression diagnosis) served as the independent grouping variable.

Interpretation for an Advanced Audience

The raincloud plot reveals a distinct separation between the two groups. Participants with a depression diagnosis demonstrated a higher mean number of poor mental health days and a greater dispersion of scores, indicating both increased frequency and variability in mental health struggles. Conversely, individuals without a diagnosis clustered around zero, with fewer and less variable poor mental health days. Although some overlap exists between groups, the elevated central tendency and variance among those diagnosed with depression suggest a robust association between clinical depression and increased mental health impairment. These findings align with previous GSS-based research identifying depression as a major determinant of mental health outcomes (Jones & Patel, 2021).

Part 2: Sampling Distribution and Confidence Intervals

Dataset Description

This portion of the assessment uses a hypothetical dataset titled Assessment_2_Data.csv (available on the Assessment 2 Canvas page). The dataset represents data collected from a simple random sample of Capella University undergraduate psychology learners. It includes demographic variables essential for descriptive and inferential statistical analysis, summarized in Table 2.

Table 2

Variables in Assessment_2_Data.csv

Variable Name	Description
ID	A unique identification number for each participant
Age	Participant’s age in years
Gender_Identity	The gender identity self-reported by the learner
IPEDS_Race_Ethnicity	Race and ethnicity as defined by the IPEDS classification system

Descriptive Statistics and Graphical Analysis

A histogram of the Age variable was created in JASP to visualize the age distribution among psychology learners. The graph indicates that most participants fall within their 30s and 40s, with fewer respondents at both the lower and upper ends of the age spectrum. The shape of the distribution appears approximately normal (bell-shaped), peaking around the mid-30s, suggesting that most learners are middle-aged adults.

Confidence Interval Calculation

Descriptive statistics for the Age variable were computed in JASP, including the sample size, mean, standard deviation, and 95% confidence interval. The results are summarized in Table 3.

Table 3

Descriptive Statistics and 95% Confidence Interval for Age

Statistic	Value
Sample Size (N)	100
Mean (M)	39.22 years
Standard Deviation (SD)	10.17
95% Confidence Interval	[37.20, 41.24]

Interpretation of Confidence Interval

The descriptive analysis indicates that the average age of participants was 39.22 years (SD = 10.17). The 95% confidence interval (37.20 to 41.24 years) suggests that there is a 95% probability that the true mean age of all Capella University undergraduate psychology learners lies within this range. These findings imply that the sample accurately reflects the broader population of Capella psychology students, assuming the sampling method adhered to principles of random selection (Gravetter & Wallnau, 2021).

Population Generalization

Given that the dataset was based on a simple random sample, it is reasonable to generalize these findings to the population of all Capella University undergraduate psychology learners. The age distribution suggests that the program primarily attracts adult learners, many of whom may be pursuing psychology degrees later in life or as a career transition. Such demographic patterns are consistent with national data on non-traditional students in online higher education (National Center for Education Statistics [NCES], 2023).

APA-Formatted Summary

A descriptive statistical analysis of the Age variable among Capella University undergraduate psychology learners demonstrated that participants (N = 100) had an average age of M = 39.22 years (SD = 10.17). The 95% confidence interval for the mean age ranged from 37.20 to 41.24 years, indicating that we can be 95% confident the true population mean age falls within this interval. These findings can be generalized to the larger population of Capella undergraduate psychology students, assuming random sampling procedures were properly implemented.

References

Gravetter, F. J., & Wallnau, L. B. (2021). Statistics for the behavioral sciences (11th ed.). Cengage Learning.

Jones, A. R., & Patel, N. K. (2021). Depression, stress, and social factors among adults: Insights from the General Social Survey. Journal of Mental Health Research, 18(3), 245–259. https://doi.org/10.1080/09638237.2021.1927890

PSYC FPX 3700 Assessment 2

National Center for Education Statistics. (2023). Digest of education statistics: Nontraditional students in higher education. U.S. Department of Education. https://nces.ed.gov

Smith, J. L., Brown, E. M., & Nguyen, T. Q. (2022). Adult mental health and demographic influences: A GSS-based analysis. American Journal of Psychological Studies, 27(2), 102–118.