# Descriptive and Inferential Statistics

## Inferential Statistics

### Questions

**Question 1 out of 8.**

Our data come from _______, but we really care most about ______.

- theories; mathematical models
- samples; populations
- populations; samples
- subjective methods; objective methods

**Question 2 out of 8.**

A random sample

- is more likely to be representative of the population than any other kind of sample.
- is always representative of the population.
- allows you to directly calculate the parameters of the population.
- all of the above are true.
- all of the above are false.

**Question 3 out of 8.**

When participants who arrive for a research study are put into treatment groups on the basis of chance,

- random sampling has occurred.
- random assignment has occurred.
- the statistical conclusions will also be absolutely correct.
- the research findings will be compromised because you should never randomly assign to groups.

**Question 4 out of 8.**

Uncertainty regarding conclusions about a population can be eliminated if you

a. use a large random sample.

b. obtain data from all members of the population.

c. depend upon the t-distribution.

d. both a and b.

**Question 5 out of 8.**

Which of the following is (are) true? Using a random sample

- is to accept some uncertainty about the conclusions.
- enables you to calculate statistics.
- is to risk drawing the wrong conclusions about the population.
- biases your results.

**Question 6 out of 8.**

A random sample is one

- that is haphazard.
- that is unplanned.
- in which every sample of a particular size has an equal probability of being selected.
- that ensures that there will be no uncertainty in the conclusions.

**Question 7 out of 8.**

Which of the following is a random sample of a college student body?

- Every fifth person coming out of the Campus Center between 8:30am and 10:00am.
- Lisa Meyer, Todd Jones, and Maria Rivera, whose ID numbers were picked from a table of random numbers.
- Every 20th person in the student directory.
- All are examples of random samples.

**Question 8 out of 8.**

A biased sample is one that

- is too small.
- will always lead to a wrong conclusion.
- will likely have certain groups from the population over-represented or under-represented due only to chance factors.
- will likely have groups from the population over-represented or under-represented due to systematic sampling factors.
- is always a good and useful sample.