How to Measure Heteroscedasticity in Regression?

[This article was first published on Methods – finnstats, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Heteroscedasticity in Regression, one of the easiest ways to measure heteroscedasticity is while using the Breusch-Pagan Test.

The test is mainly used to identify if heteroscedasticity is present in a regression analysis.

This tutorial explains how to execute a Breusch-Pagan Test in R.

pipe operator in R-Simplify Your Code with %>% »

Heteroscedasticity in Regression

Step 1: Fit a regression model.

First, we will fit a regression model using Wind as the response variable and Temp and Month as the two explanatory variables.

load the airquality dataset


fit a regression model

model <- lm(Wind~Temp+Month, data= airquality)

view model summary

How to find dataset differences in R Quickly Compare Datasets »



lm(formula = Wind ~ Temp + Month, data = airquality)
    Min      1Q  Median      3Q     Max
-8.5401 -2.4133 -0.2177  2.0019  9.7670
            Estimate Std. Error t value Pr(>|t|)   
(Intercept) 23.14224    2.15939  10.717  < 2e-16 ***
Temp        -0.17322    0.02978  -5.817 3.49e-08 ***
Month        0.04382    0.19898   0.220    0.826   
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Multiple R-squared:   0.21,           Adjusted R-squared:  0.1995
F-statistic: 19.94 on 2 and 150 DF,  p-value: 2.097e-08

Kruskal Wallis test in R-One-way ANOVA Alternative »

Step 2: Perform a Breusch-Pagan Test.

Here we are going to measure the heteroscedasticity for that we can make utilize a Breusch-Pagan Test.

load lmtest library


Execute Breusch-Pagan Test


               studentized Breusch-Pagan test

data:  model
BP = 2.1131, df = 2, p-value = 0.3477

The test statistic is 2.1131 and the corresponding p-value is 0.3477. Since the p-value is greater than 0.05, we cannot reject the null hypothesis.

This indicates that we do not have sufficient evidence to reject the null hypothesis or sufficient evidence to say heteroscedasticity is present in the regression model.

aggregate Function in R- A powerful tool for data frames »

The post How to Measure Heteroscedasticity in Regression? appeared first on finnstats.

To leave a comment for the author, please follow the link and comment on their blog: Methods – finnstats. offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)