Question

To investigate the effect of Age (in years) and Smoking Status (Group 1: Non-Smokers, Group 2: Smokers) on Systolic Blood Pressure (in mmHg), the following data were collected:

The txt from the table in the image is provided below:

on-smoker     Smoker    
Patient Age (X) Systolic Blood Pressure (Y) Patient Age (X) Systolic Blood Pressure (Y)
1 40 120 1 35 128
2 45 124 2 42 135
3 50 130 3 48 142
4 55 132 4 53 148
5 60 138 5 58 155
6 65 142 6 62 158
7 70 145 7 68 165
8 75 150      

 


(i) Fit a multiple regression model.

(ii) Obtain the individual regression models for Non-Smokers and Smokers separately based on the main model.

(iii) Test the significance of the overall fitted regression model at the 5% level of significance.

25 Mar 2026
Answer :
Word Count : 1444
Let us solve this step by step manually. We are given data for Age (X) and Systolic Blood Pressure (Y) for Non-Smokers and Smokers. We are asked to fit a multiple regression model with Smoking Status as a categorical variable and Age as a continuous variable. --- ### Step 1: Encode Smoking Status Let us define a dummy variable: [ S = \begin{cases} 0 & \text{Non-Smoker} \ 1 & \text{Smoker} \end{cases} ] We have 8 Non-Smokers and 7 Smokers. --- ### Step 2: Set up the multiple regression model The model is: [ Y = \beta_0 + \beta_1 X + \beta_2 S + \varepsilon ] Where: * (Y) = Systolic BP * (X) = Age * (S) = Smoking Status (0 = Non-Smoker, 1 = Smoker) We need to calculate (\beta_0, \beta_1, \beta_2) using the least squares method. --- ### Step 3: Calculate necessary sums Combine all data: | Patient | X | Y | S | | ------- | -- | --- | - | | 1 | 40 | 120 | 0 | | 2 | 45 | 124 | 0 | | 3 | 50 | 130 | 0 | | 4 | 55 | 132 | 0 | | 5 | 60 | 138 | 0 | | 6 | 65 | 142 | 0 | | 7 | 70 | 145 | 0 | | 8 | 75 | 150 | 0 | | 1 ___ ____ __________ ____ ______ _____.
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