I am writing project talking about NFL comparing how the number of passes attemp

Question

I am writing project talking about NFL comparing how the number of passes attempted by a quarterback and how it correlates with the number of touchdown or interception thrown. Below is what my prof suggest I do. Can you help elaborate on it?

Please use your suggested cutoff of 300 pass attempts to eliminate running backs/punters/etc. who only threw one pass. Your population is then all quarterbacks who throw enough passes to matter over an entire season, and you are assuming 2016 is representative of all years. You will do two separate linear regressions: one with touchdowns vs. pass attempts and one with interceptions vs. pass attempts. You can estimate the slope of both lines

Explanation / Answer

Let me explain you my understanding of this problem statement:

First he is saying to eliminate the players who threw less than 300 pass attempts from you data set. And you only need to consider year 2016 to prove your hypothesis.

Now he needs to find the correlation one with touchdowns vs Pass attempts and one with interceptions vs pass attempts.

Linear regression line Y = aX + b

we will derive 2 equations Y being the touchdowns and interceptions and X being pass attempts.

In R

We can perform linear regression using following syntax in R

data <- read.csv(“file path”, sep=“”)

fit <- lm(Y~X , data = data)

summary(fit)

Summary provides us with all vital informations like equation of line and also gives us the p value attached to the coefficient (pass attempts in our case) which helps us to determine the significance of that parameter in contributing to our model. High p value means low significance.

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