id stringlengths 40 40 | repo_name stringlengths 5 110 | path stringlengths 2 233 | content stringlengths 0 1.03M ⌀ | size int32 0 60M ⌀ | license stringclasses 15
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|---|---|---|---|---|---|
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | cartmanG/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | azilnoor/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | xueping312/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | NicoloPernigo/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | dpc5090/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | hyperbeam2/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | fehtemam/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | roysuchandra/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | githubfun/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | SteveLi90/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | CarlosJunior4763/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | FreeSchoolHackers/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | bblount/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | emiels/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | richardwei2008/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | tjautio/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | ogarces/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | lostinmunich/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | GundamYeti/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | xujiawei1993/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | martik617/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | menghaur/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | bbaczyk/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | v-nayjack/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | kevinbgunn/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | pmijar/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | k3140285kop/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | AmirtharajBritto/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | hfe2567/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | yewenhe0904/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | lcuellar/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | iac7/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | kamfonas/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
93474a5f0d9cae1613a31b905de6ff765528670d | tomwhite/hellbender | src/main/resources/org/broadinstitute/hellbender/tools/recalibration/BQSR.R | library("ggplot2")
library(gplots)
library("reshape")
library("grid")
library("tools") #For compactPDF in R 2.13+
library(gsalib)
if ( interactive() ) {
args <- c("NA12878.6.1.dedup.realign.recal.bqsr.grp.csv", "NA12878.6.1.dedup.realign.recal.bqsr.grp", NA)
} else {
args <- commandArgs(TRUE)
}
data <- read.cs... | 7,075 | bsd-3-clause |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | goransta/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | DongliLiu/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | josephvalvo/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | srimanvs/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | momoa16/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | ylchang/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | datacamp/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | lkngin/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | sanjogar/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | ome9ax/datascience | vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | brezniczky/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | TeddyTiome/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | ashishchandan/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | jdgriffin/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | Jambiol/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | aruneral01/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | rflsierra/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | shrekodn/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | LadyoftheWater/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | Masabeca/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | Echolumos/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | ABourcevet/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | Jackson85/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | boxcarrovers/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | lcoulibaly/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | dasjpatel15/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | jamesoliver1981/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | tapangoel1994/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | MartinDavila/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | mmfern01/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | akhilK17/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | horrorkumani/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | mhdella/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | gloriaShopping/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | HeatherStamps/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | fanying2015/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | lblinder/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | melchiadesblanco/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | anfe67/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | ajaen/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | fvdgeer/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | warszawiak/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | wengers11/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | fainafr/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | fanglu01/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | derwinmcgeary/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | lipnerova/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | LuisRuizDelFresno/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | drnuance/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | johnsonzhj/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | anupkumardixit/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | Dineshvmr/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | DirgniF/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | johnneyb/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | patricksu/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | gringwald/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | tvijay333/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | xyzhang89/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | ilo10/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | niloynibhochaudhury/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | AnyaMit/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | ZiTUNG/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | rdemorae/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | korotkyn/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | rScientist/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
49361ccfee0095ac83cfe4f3d2d7090c829cd9e7 | owenyang83/swirl_courses | Regression_Models/Variance_Inflation_Factors/vifSims.R | makelms <- function(x1, x2, x3){
# Simulate a dependent variable, y, as x1
# plus a normally distributed error of mean 0 and
# standard deviation .3.
y <- x1 + rnorm(length(x1), sd = .3)
# Find the coefficient of x1 in 3 nested linear
# models, the first including only the predictor x1,
# the second x1 a... | 1,304 | gpl-3.0 |
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