The CAP® examination is a 100-item written test composed of multiple-choice questions with four options.
There is only one correct or best answer for each question. Candidates will be given three (3) hours to
complete the examination.
Sample Test Questions
The following sample test questions were developed by subject matter experts in the analytics field. The
correct answer key at the end of this list of questions provides the correct answers to each question. These
sample questions will never appear in an actual CAP® examination and are provided as an example of
the type of question found on the examination.
The 24 questions published here are intended to familiarize certification candidates and potential certification
candidates with the format of the questions that appear on the CAP® examination. They are also intended to
provide a sample of the content (knowledge and skill) assessed by the CAP® examination. These questions
are not intended as a self-assessment instrument nor should they be used to predict success or failure on the
CAP® exam. Candidates and potential candidates should bear in mind that the CAP® examination is a “pass/
fail” assessment and that passing does not require correct answers to all questions. It should also be kept in
mind that examination preparation efforts will likely increase knowledge and sharpen skills.
1. Which of the following BEST describes the data and information flow within an organization?
a) Information assurance
b) Information strategy
c) Information mapping
d) Information architecture
2. A multiple linear regression was built to try to predict customer expenditures based on 200
independent variables (behavioral and demographic). 10,000 rows of data were fed into a
stepwise regression, each row representing one customer. 1,000 customers were male, and 9,000
customers were female. The final model had an adjusted R-squared of 0.27 and seven independent
variables. Increasing the number of rows of data to 100,000 and rerunning the stepwise regression
will most likely:
a) have no impact upon the adjusted R-squared.
b) increase the impact of the male customers.
c) change the heteroskedasticity of the residuals in a favorable manner.
d) decrease the number of independent variables in the final model.
3. A clothing company wants to use analytics to decide which customers to send a promotional
catalogue in order to attain a targeted response rate. Which of the following techniques would be the
most appropriate to use for making this decision?
a) Integer programming
b) Logistic regression
c) Analysis of variance
d) Linear regression
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