15.071 | Spring 2017 | Graduate

The Analytics Edge

2.2 The Statistical Sommelier: An Introduction to Linear Regression

2.2 The Statistical Sommelier: An Introduction to Linear Regression

Quick Question

Use the dataset wine.csv to create a linear regression model to predict Price using HarvestRain and WinterRain as independent variables, like you did in the previous quick question. Using the summary output of this model, answer the following questions:

Is the coefficient for HarvestRain significant?

 
 
 

Explanation You can create the model and look at the summary output with the following command: model = lm(Price ~ WinterRain + HarvestRain, data=wine) summary(model) From the summary output, you can see that HarvestRain is significant (two stars), but WinterRain is not (no stars).

Is the coefficient for WinterRain significant?

 
 
 

Explanation You can create the model and look at the summary output with the following command: model = lm(Price ~ WinterRain + HarvestRain, data=wine) summary(model) From the summary output, you can see that HarvestRain is significant (two stars), but WinterRain is not (no stars).

Note that you will need to answer both questions before checking your answers.

Course Info

As Taught In
Spring 2017
Level
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Lecture Videos
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Problem Sets with Solutions