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HW3 (1) University of Texas, Dallas DATA MANAG 6326

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1. Breakfast Cereals. Use the data for the breakfast cereals example discussed in class to explore and summarize the data as follows: a. Import the data to R. Copy the R code used below. cereals.df... <- read.csv("Cereals.csv", header = TRUE) b. Which variables are numerical? Which variables are categorical? Variable Type name Categorical mfr Categorical type Categorical calories Numerical protein Numerical fat Numerical sodium c. Compute the mean, median, min, max, and standard deviation for each of the numeric variables. Copy the code used and the resulting table below data.frame(mean=sapply(cereals.df[,4:16], men), sd=sapply(cereals.df[,4:16], sd), min=sapply(cereals.df[,4:16], min), max=sapply(cereals.df[,4:16], max), median=sapply(cereals.df[,4:16], median), length=sapply(cereals.df[,4:16], length), miss.val=sapply(cereals.df[,4:16], function(x) sum(length(which(is.na(x)))))) After removing the missing values in the columns d. Plot a histogram for each of the numeric variable. Copy the code used and the generated charts below. Based on the histograms and summary statistics, which variables have the largest variability? Which variables seem skewed? [Show More]

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