Report here the mean absolute deviation you calculated. Provide your answer to two decimal places.

According to this regression model, on average, how much more/less does a male employee earn as compared to a female employee with the same attributes? Enter a positive number if males earn more on average than females, and a negative number if males earns less on average than females. Provide your answer to three decimal places.

According to this regression model, on average, how much more/less does an Explorer earn as compared to a Diplomat? Enter a positive number if an Explorer earns more on average than a Diplomat, and a negative number if an Explorer earns less on average than a Diplomat. Provide your answer to three decimal places.

Enter below an R command that will output a plot that indicates whether region is likely to be a good predictor of charges. That is, it should indicate something about the relationship between charges and region.

Enter an R expression to run a regression to predict Salary using all the other variables (aside from Sales_Rep).

Provide your actual confusion matrix below. Don’t worry if you confusion matrix doesn’t look perfect below. As long as I can figure out what it is, that’s fine.

Following the traditional statistical approach to regression, which of the following is the most appropriate next step to take?

Show your work — that is, your R commands and output — for the data analytics regression you just did. From partitioning the data through calculating the summary measures. I will review this work for partial credit if your answer to the three previous questions are incorrect.

What is the specificity of the model? That is, given that the individual actually did not have a stroke, what’s the probability your model predicts no stroke? Again, provide your answer to four decimal places.

Report here the mean absolute percent error you calculated. Provide your answer in the form of a fraction, to four decimal places.