Research Methods Report: Analyzing Student Data and Statistics

This report presents a statistical analysis of student data collected through a questionnaire. The analysis includes calculating the mean and standard deviation of CGPA, descriptive statistics, and a pie chart illustrating the reasons students attend university. The report also calculates z-scores to determine outliers and assess the significance of CGPA values. Furthermore, it explores the relationship between CGPA and total study hours using scatter plots, correlation coefficients, and the coefficient of determination. Linear regression is employed to model the relationship between the variables, with hypothesis testing conducted to assess the significance of the slope coefficient. The report concludes with a discussion of the key findings, including the positive correlation between study hours and CGPA, and highlights the importance of meeting the assumptions of linear regression. Additionally, factors influencing post-secondary education enrolment are discussed based on another study, including youth health, math scores, parental education, and household income.