May 2019
Beginner to intermediate
266 pages
5h 57m
English
Content preview from Hands-On Exploratory Data Analysis with R
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Multi-factor variance analysis
To understand the correlation between the variables, it is important to understand the interaction between all the variables within the dataset. Let's focus on multi-factor variance analysis of the data frame specified with the help of the following steps:
- Create an aggregate value of the data frame with respect to the mpg and displacement values mentioned as follows:
> d <- aggregate(mpg ~ displacement, data = Autompg, FUN = mean)> d displacement mpg 1 68.0 29.00000 2 70.0 20.23333 3 71.0 31.50000 4 72.0 35.00000 5 76.0 31.00000 6 78.0 32.80000 7 79.0 32.18333 8 80.0 21.50000 9 81.0 35.10000 10 83.0 32.00000 > print(abs(d[[2]][1]-d[[2]][2])) [1] 8.766667
- Now, let's build a model with the lm function ...
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