Week 2 Quiz of Predictive Modeling and Analytics

Which type of target variable are we dealing with in linear regression?

We cannot perform linear regression unless both the target variable and predictor variables are continuous.

Given the graph below, we see a red best fit line has been applied to map the trend of the data. We also see specific clusters of points have been circled out and labeled 1, 2, and 3. Which cluster has the greatest residual value magnitude ( ignore positive and negative signs, just compare numeric values ) ?

Calculate the sum of squared errors for the validation data set given below. Recall, you square the residual values before summing them .

Why can multicollinearity cause problems in multiple regression? (Select all that apply.)

How many transformed variables can we create based on one predictor variable?

The figures here show the scatter plot with different data transformations. The top left figure is the scatter plot of list price vs SQFT when no transformation is performed. The top right one shows the scatter plot when a log transformation is applied to SQFT. The bottom left figure shows the plot where a log transformation is applied to list price, while the bottom right figure shows the plot where log transformation is applied to both variables.

Which one gives us better model fit?

What do you achieve when you apply a log transformation to a variable in your data set?