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Adjusted R2 = 1 - [(1 - R2) x (n - 1)} / (n - p - 1)] where
n: Number of observations = 4,701 and
p = Number of independent variables = 6
Adjusted R2 = 1 - [(1 - R2) x (4,701 - 1)} / (4,701 - 6 - 1)] = 1 - [(1 - R2) x 4,000} / 4,694] = 1 - [0.8522 x (1 - R2)]
Model 1: R2 = 0.143
Adjusted R2 = 1 - [0.8522 x (1 - 0.143)] = 1 - (0.8522 x 0.857) = 1 - 0.730 = 0.270
Model 2: R2 = 0.168
Adjusted R2 = 1 - [0.8522 x (1 - 0.168)] = 1 - (0.8522 x 0.832) = 1 - 0.709 = 0.291
Model 3: R2 = 0.143
Adjusted R2 = 1 - [0.8522 x (1 - 0.124)] = 1 - (0.8522 x 0.876) = 1 - 0.747 = 0.253
hey guy, i need your help in this question , thank you soooo much! More Info...
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I only need Question 4 (Image above) answered. I am
providing you with the rest of the questions and other information
for background information since it is necessary to answer Question
4. I do not need answers to Q1, 2 and 3 - only for Q4
Background information for the question:
The dataset weightloss.dta contains information on 77 patients
randomised to undertake one of three diets (referred to as diet A,
B and C). Some background information is also available,...