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In: Statistics and Probability

Problem 1, Total / 10 ( 1 each) Fill in the letter for each term. Each...

Problem 1, Total / 10 ( 1 each) Fill in the letter for each term. Each term is used exactly once. Write clearly.

1. Akaike Information Criterion (AIC) ________

2. Dummy variable _________

3. Imputation _________

4. Interaction __________

5. Leave-One-Out __________

6. Overfitted ______

7. Quantile-Quantile _________

8. Stepwise Method _________

9. Training Set ________

10. Variance Inflation Factor ___________

A) Used to find a good model according to some criterion. Works by repeatedly 'dropping' or 'adding' one term to the current model.

B) Used to specify whether an observation is in a specific category, rather than some baseline.

C) Term for a model that applies well to the data set given, but poorly to new observations.

D) The part of the data used to make a model in a cross-validation.

E) Plot used to explore any deviations from normality (or other specified distribution) in a collection of values.

F) A measure to compare statistical models. Considers both model fit and complexity.

G) A special case of K-fold cross validation using training sets of N-1 observations.

H) A regression term made of two (or more) variables, multiplied together.

I) A measure of co-linearity of a regression term.

J) General term for methods of replacing missing data

Expert Solution

1. Akaike Information Criterion (AIC) - F) A measure to compare statistical models. Considers both model fit and complexity.

2. Dummy variable - B) Used to specify whether an observation is in a specific category, rather than some baseline.

3. Imputation - J) General term for methods of replacing missing data

4. Interaction - H) A regression term made of two (or more) variables, multiplied together.

5. Leave-One-Out - D) The part of the data used to make a model in a cross-validation

6. Overfitted - C) Term for a model that applies well to the data set given, but poorly to new observations.

7. Quantile-Quantile - E) Plot used to explore any deviations from normality (or other specified distribution) in a collection of values.

8. Stepwise Method - A) Used to find a good model according to some criterion. Works by repeatedly 'dropping' or 'adding' one term to the current model.

9. Training Set - G) A special case of K-fold cross validation using training sets of N-1 observations.

10. Variance Inflation Factor - I) A measure of co-linearity of a regression term.

orchestra answered 2 years ago

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