Multiple regression is a powerful tool that creates a linear model using more than one independent variable.

8. Question 8 Multiple regression is a powerful tool that creates a linear model using more than one independent variable. 1 / 1 point   True   False

If variables are perfectly correlated, then the correlation will always be 1.

4. Question 4 If variables are perfectly correlated, then the correlation will always be 1.  1 point   True   False

We can use undo for changes performed by a macro.

5. Question 5 We can use undo for changes performed by a macro. 1 / 1 point   True   False

Once you set a break point in macro, you can’t remove it.

5. Question 5 Once you set a break point in macro, you can’t remove it. 1 / 1 point   True   False

In unsupervised learning, we do not need the presence of a group label since we let algorithms tell us which group our observations fall into.

6. Question 6 In unsupervised learning, we do not need the presence of a group label since we let algorithms tell us which group our observations fall into. 1 / 1 point   True   False

The biggest difference between supervised and unsupervised machine learning is that supervised machine learning requires the identification of a dependent variable, whereas unsupervised machine learning does not need to a dependent variable identified.

6. Question 6 The biggest difference between supervised and unsupervised machine learning is that supervised machine learning requires the identification of a dependent variable, whereas unsupervised machine learning does not need to a dependent variable identified. 1 / 1 point   True   False…

For regression with categorical dependent variable, the dependent variable is coded as an indicator variable.

7. Question 7 For regression with categorical dependent variable, the dependent variable is coded as an indicator variable. 1 / 1 point   True   False

Overfitting refers to the situation when a model does a better job of predicting the dependent variable for data that wasn’t used to create the model, than it does of predicting the dependent variable for the data that was used to create the model.

9. Question 9 Overfitting refers to the situation when a model does a better job of predicting the dependent variable for data that wasn’t used to create the model, than it does of predicting the dependent variable…

For regression with categorical dependent variable, the dependent variable is coded as an indicator variable.

7. Question 7 For regression with categorical dependent variable, the dependent variable is coded as an indicator variable. 1 / 1 point   True   False

What should we do if we find that a coefficient in multiple regression is insignificant?

5. Question 5 What should we do if we find that a coefficient in multiple regression is insignificant? 1 / 1 point   We should make it become significant.   We should keep it in our…