This report presents a quantitative analysis of business data, focusing on the relationship between take-home pay and weekly food expenditure. The analysis employs stratified random sampling and addresses potential data collection issues. Descriptive statistics, including histograms and numerical summaries, reveal a positive skew in the data. Regression analysis indicates a strong positive correlation between the variables, with a correlation coefficient of 0.90. The regression equation (y = 40.86 + 0.31x) suggests that for every $1 increase in take-home pay, weekly food expenditure increases by $0.31. Hypothesis testing confirms the statistical significance of the regression model. The report concludes that the variables are strongly correlated, validating the understanding that food expenditure is a function of income. Desklib offers a variety of similar solved assignments and past papers for students.