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here is the code for the questions use this code for questiosn 1 and 2 par(mfrow=c(1,2)) # one row with 2 graphics on a single

here is the code for the questions

use this code for questiosn 1 and 2

par(mfrow=c(1,2)) # one row with 2 graphics on a single graphics window

# the above line will open a blank graphics window - leave open while running the next 2 lines.

hist(train$GrLivArea, breaks=20, main = "Square Feet",

cex.main = 2, xlab = "Square Feet", ylab = "Frequency")

hist(log(train$GrLivArea), main = "Log Square Feet",

cex.main = 2, xlab = "Log Square Feet", ylab = "Frequency")

here is the code for the rest of the questions

par(mfrow=c(1,2)) # one row with 2 graphics on a single graphics window

plot(train$GrLivArea, train$SalePrice, xlab = "Square Feet", ylab = "Sale Price")

plot(log(train$GrLivArea), log(train$SalePrice), xlab = "Log Square Feet", ylab = "Log Sale Price")

questions

Q1. Highlight one. Refer to the histograms. What is the shape of the Square footage distribution? Skewed left / skewed right / mostly unimodal and symmetric Q2. Highlight one. What is the shape of the log square footage distribution? Skewed left / skewed right / mostly unimodal and symmetric Q3. Paste your 2 scatterplots (from the single graphics window) to fit in the rectangle below. (I recommend screenshotting the graphs.) Q4. From the scatterplot above (on left), describe the bivariate distribution of square footage and sales price. Highlight one: cone/fan-shape, with data becoming more variable from left to right and two outliers in square footage OR cone/fan-shape, with data becoming less variable from left to right and two outliers in square footage OR linear, with constant variance and no obvious outliers Q5. Now describe how taking the log transform of both variables changes the bivariate distribution in at most 2 sentences. Type answer in blue font. Q6. Paste the 3 lines of code that produced your scatterplots below.

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