This analysis examines whether employees’ communication skills significantly improved after attending a professional communication training program. Using a paired design, we compared pre-training and post-training scores for 150 employees. Normality was assessed through visual checks and the Shapiro–Wilk test, and a dependent t-test was conducted to determine statistical significance and effect size. ________________________________________

This report presents the analysis for Research Scenario 2 from Assignment 6, which investigates whether there is a statistically significant difference in customer satisfaction scores between customers served by human agents and those assisted by an AI chatbot. Due to violations of normality assumptions and the presence of outliers, the non-parametric Mann-Whitney U test was employed. The report includes descriptive statistics, visualizations (histograms and boxplots), normality checks using the Shapiro-Wilk test, and effect size estimation to assess the magnitude of the observed difference.

This analysis investigates whether Medication A significantly reduces headache days compared to Medication B. The report includes hypothesis testing, normality checks, Independent t-test results, effect size interpretation, and APA-style reporting.

This report presents a Chi-Square Goodness-of-Fit Test for Research Scenario 1 (Assignment 4). The analysis examines whether dessert preferences (chocolate cake, vanilla cheesecake, tiramisu) among 548 participants differ from an equal distribution. Results indicate a statistically significant difference, with chocolate cake being the most preferred option. Effect size (Cohen’s W = 0.31) suggests a moderate deviation from equal preference.

This report presents a comprehensive statistical analysis exploring the relationship between Antivirus and Laptop scores. Using descriptive statistics, histograms, normality tests, and Pearson correlation, the study confirms a strong positive association between the two variables. All results are visualized and interpreted in a clear, beginner-friendly format, making this report suitable for educational and analytical purposes.

This publication presents a comprehensive statistical analysis of two continuous variables: Minutes and Drinks. Using R, I explored the data through descriptive statistics, histograms, and normality tests (Shapiro-Wilk). Both variables showed positive skewness and leptokurtic distributions, indicating non-normality. To assess the relationship, I conducted both Spearman and Pearson correlation tests. Results revealed a strong, positive, and statistically significant correlation (Spearman ρ = 0.92, Pearson r = 0.95, p < .001). This suggests that as time spent (Minutes) increases, the number of drinks consumed also increases. The report includes: Cleanly formatted R code and outputs Visualizations (histograms and scatterplots with regression line) Clear interpretation of results written as comments within the R script This RPubs publication demonstrates how to combine data visualization, normality testing, and correlation analysis into a reproducible workflow using R Markdown.

This report presents the results of a Chi-Square Test of Independence conducted to examine the association between parent type (mother, father) and uniform design preference (Design A, Design B). The analysis includes a contingency table, test output, and an effect size calculation using Cramér’s V. The results indicate no statistically significant association between the two variables, with a small effect size.

This report presents the results of a Chi-Square Goodness-of-Fit Test conducted to examine whether participants' cake type preferences (Cheesecake, ChocoCake, Tiramisu) differed from expected proportions. The analysis includes observed frequencies, statistical significance, and effect size interpretation.