From 19c2c8704e249f43ce930515484cd19244c4235a Mon Sep 17 00:00:00 2001 From: caes Date: Mon, 30 Jan 2017 21:27:44 -0500 Subject: [PATCH] more answers --- hw2/answers | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/hw2/answers b/hw2/answers index 03cf735..30f36ac 100644 --- a/hw2/answers +++ b/hw2/answers @@ -13,8 +13,8 @@ linear model. X 3 = Gender (1 for Female and 0 for Male), X 4 = Interaction between GPA and IQ, and X 5 = Interaction between GPA and Gender. The response is starting salary after graduation (in thousands of dollars). -Suppose we use least squares to fit the model, and get β 0 = 50, β 1 = -20, β 2 = 0.07, β 3 = 35, β 4 = 0.01, β 5 = −10. +Suppose we use least squares to fit the model, and get β₀ = 50, β₁ = +20, β₂ = 0.07, β₃ = 35, β₄ = 0.01, β₅ = −10. (a) Which answer is correct, and why? i. For a fixed value of IQ and GPA, males earn more on average @@ -41,10 +41,10 @@ Suppose we use least squares to fit the model, and get β 0 = 50, β 1 = 4. I collect a set of data (n = 100 observations) containing a single predictor and a quantitative response. I then fit a linear regression model to the data, as well as a separate cubic regression, i.e. Y = -β 0 + β 1 X + β 2 X 2 + β 3 X 3 + . +β₀ + β₁ X + β₂ X² + β₃ X³ + . (a) Suppose that the true relationship between X and Y is linear, - i.e. Y = β 0 + β 1 X + . Consider the training residual sum of + i.e. Y = β₀ + β₁ X + . Consider the training residual sum of squares (RSS) for the linear regression, and also the training RSS for the cubic regression. Would we expect one to be lower than the other, would we expect them to be the same, or is there