For this study, I examined whether student type (domestic or international) is associated with pet ownership (yes or no). Because both variables are categorical, I conducted a Chi-Square Test of Independence to determine whether a relationship exists between them. The null hypothesis stated that there is no association between student type and pet ownership, while the alternative hypothesis stated that an association exists. The results of my analysis determined whether pet ownership differs based on student status. If the results were statistically significant, I rejected the null hypothesis and concluded that a relationship exists; if not, I concluded that the variables are independent. This analysis provides insight into student needs and can help the university better plan for pet-friendly housing and related services.

For this study, I examined students’ beverage preferences to help campus dining services make informed decisions about drink offerings and resource allocation. Students selected their preferred beverage from four options: tea, coffee, soda, or water. The purpose of my analysis was to determine whether the observed distribution of beverage preferences differed from the expected distribution provided in the research scenario. Because the variable favorite drink is categorical with four levels, I conducted a Chi-Square Goodness-of-Fit test. The null hypothesis stated that there would be no difference between the observed and expected frequencies, while the alternative hypothesis stated that a difference would exist. The results of the chi-square goodness-of-fit test were statistically significant, χ²(3) = 45.53, p < .001, indicating that the observed distribution of beverage preferences was significantly different from the expected distribution. Therefore, I rejected the null hypothesis. I also calculated Cohen’s W to measure the strength of the effect, which was 1.73, indicating a strong effect size. Overall, my findings suggest that students do not prefer the beverages equally and that certain drinks are favored more than others. These results can help campus dining services better allocate resources, reduce waste, and align beverage offerings with student preferences.

This project analyzes the relationships between study habits, exam performance, screen time, and sleeping hours using correlation analysis in R. Two datasets were imported from Excel files, and descriptive statistics were calculated to summarize each variable. Histograms and Shapiro–Wilk tests were used to assess normality, which guided the selection of Spearman correlations for both analyses. The results showed a strong positive relationship between study hours and exam scores, indicating that increased study time is associated with higher exam performance. A strong negative relationship was also found between screen time and sleeping hours, suggesting that higher screen use is linked to reduced sleep. Scatterplots with regression lines were created to visually confirm the direction, strength, and linearity of each relationship.

This project analyzes the relationships between study habits, exam performance, screen time, and sleeping hours using correlation analysis in R. Two datasets were imported from Excel files, and descriptive statistics were calculated to summarize each variable. Histograms and Shapiro–Wilk tests were used to assess normality, which guided the selection of Spearman correlations for both analyses. The results showed a strong positive relationship between study hours and exam scores, indicating that increased study time is associated with higher exam performance. A strong negative relationship was also found between screen time and sleeping hours, suggesting that higher screen use is linked to reduced sleep. Scatterplots with regression lines were created to visually confirm the direction, strength, and linearity of each relationship.