10. The study aimed to study the prediction of BMI (kg/m) using mid-upper arm circumference, MUAC, (cm). The data are stored in 'muac.csv'. a) Fit a simple linear regression model to the dataset and plot the fitted regression line on the graph obtained in (a). Report the estimates of the regression coefficients. b) Find the coefficient of determination and comment on the fitness of the model. c) Interpret the slope quantitatively. d) Find the predicted values and residuals of the first 2 observations. e) Find SSE and MSE. f) Find the standard errors of the intercept and the slope. g) Test at the 5% level whether MUAC is effective in explaining the variation in BMI. h) Construct at 90% confidence interval for the true slope. Hence, test at the 10% level of significance whether the slope is 1. i) Construct a 95% confidence interval mean BMI at MUAC = 25 cm. j) Construct a 95% prediction interval for the difference between the average BMI of two groups of subjects. The first group of subjects have MUAC as 25, 26 and 28. The second group of subjects have MUAC as 27 and 29.