1. In building regression models, nominal variables, such as Gender or Ethnicity,

a. can be added to the model by assigning numbers to each label.

b. cannot be included in regression models because they are not numeric.

c. are easiest to include for binary variables where yes = 1 and no = 0

d. none of the above.

2. a discriminant function

a. is used to estimate the probability that a case is in a particular group

b. separate cases into many groups or clusters.

c. is a function that separates the majority of values into two groups.

d. all of the above

3. errors in classification models

a. are incorrect classifications

b. May be measured in terms of various types of error rates

c. are not measured in terms of the size of the error

d. all of the above

4. methods that estimate the probability or likelihood that a case belongs to a group or incomplete without

a. The casual analysis that explains the contribution of each variable

b. a decision rule to how to assign cases to groups based upon the probability

c. measure of the error of the probability

d. nothing else is needed since you assign the case to the group if the probability exceeds 50%

5. among methods for binary classification

a. logistic regression is most accurate

b. discriminant functions work best

c. KNN is the method of last resort

d. they all work reasonably well