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R-Studio help download.file(http://www.openintro.org/stat/data/mlb11.RData, destfile = mlb11.RData) load(mlb11.RData) Exercises. 4.Make a new variable, high_BA , to represent teams that hit for a batting average of 0.270

R-Studio help

download.file("http://www.openintro.org/stat/data/mlb11.RData", destfile = "mlb11.RData")

load("mlb11.RData") Exercises.

4.Make a new variable, high_BA , to represent teams that hit for a batting average of 0.270 or more. How many teams fit into this group?

### Enter code here

15. You can use favstats to get the summary statistics within each high_BA group, and bwplot() to make boxplots. For example, what appears to be the link between homeruns and high_BA? Do teams with higher batting averages tend to hit more home runs?

favstats (homeruns ~ high_BA, data = mlb11)

densityplot (~ homeruns, groups = high_BA, data = mlb11, auto.key = TRUE)

16. Repeat the code above, only using stolen bases instead of homeruns. Does there appear to be a link between stolen bases and high_BA?

### Enter code here.

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