Consider the following code chunk and output and note that NA appears in the output of lm(). X1 <- rnorm(1e2) X2 <- X1 + 3 Y <- X1 + X2 + rnorm(1e2) lm(Y ~ X1 + X2) Call: lm(formula = Y ~ X1 + X2) Coefficients: (Intercept) X1 X2 2.979 2.019 NA Which of the following statements are correct? a) Perfectly correlated regressors X1 and X2 are used. b) lm() excludes X2 from the regression so that there is a least squares solution. c) NA indicates that the model fit to the data is perfect.
Consider the following code chunk and output and note that NA appears in the output of lm(). X1 <- rnorm(1e2) X2 <- X1 + 3 Y <- X1 + X2 + rnorm(1e2) lm(Y ~ X1 + X2) Call: lm(formula = Y ~ X1 + X2) Coefficients: (Intercept) X1 X2 2.979 2.019 NA Which of the following statements are correct? a) Perfectly correlated regressors X1 and X2 are used. b) lm() excludes X2 from the regression so that there is a least squares solution. c) NA indicates that the model fit to the data is perfect.
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Consider the following code chunk and output and note that NA appears in the output of lm().
X1 <- rnorm(1e2) X2 <- X1 + 3 Y <- X1 + X2 + rnorm(1e2) lm(Y ~ X1 + X2)Call: lm(formula = Y ~ X1 + X2) Coefficients: (Intercept) X1 X2 2.979 2.019 NA
Which of the following statements are correct?
a) Perfectly correlated regressors X1 and X2 are used.
b) lm() excludes X2 from the regression so that there is a least squares solution. c) NA indicates that the model fit to the data is perfect.
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