Unit 6 Test Review

What is the difference between a population and a sample?

• A. A sample includes the entire group, while a population is a portion of that group.

• B. A population includes the entire group, while a sample is a portion of that group.

• C. A sample and a population are the same thing.

• D. A sample must be larger than the population.

Which of the following best describes sampling variability?

• Different random samples from the same population can produce different results.

• A sample always perfectly represents the population.

• Random sampling eliminates all variability.

• Sampling variability only occurs when a sample is biased.

What is the main purpose of using a random sample?

• To ensure that everyone in the population is included.

• To reduce bias and make the results more generalizable.

• To make calculations easier.

• To get a larger sample size.

Which of the following is the best method for selecting a random sample of 50 words from a paragrph with 850 words?

• Select the first 50 words of the paragraph.

• Count up how many times words are repeated 50 times.

• Assign each word a number and use a random number generator to select 50 words.

• Select 10 words from each of the 5 sentences of the paragraph.

A survey estimates that the proportion of students who prefer online learning is between 46% and 52%. Based on this confidence interval, which of the following values is a plausible estimate for the true proportion of all students who prefer online learning?

• 44%

• 50%

• 53%

• 60%

Why is bias in a study or survey a problem?

• It makes it impossible to draw any conclusions from the study.

• It can lead to misleading conclusions that do not accurately represent the population.

• Bias only affects certain populations, so we just don't include them.

• A biased study makes for silly results.

Which variable is manipulated in an experiment?

• Response variable

• Confounding variable

• Explanatory variable

• Control variable

The main difference between an observational study and an experiment is:

• A. Experiments involve random sampling, while observational studies do not.

• B. Observational studies just observe, while experiments impose treatment.

• C. Observational studies only involve surveys.

• D. Experiments always use a sample, while observational studies use the entire population.

A confounding variable is:

• A variable that explains the cause-and-effect relationship

• A factor that influences both the explanatory and response variables, making it difficult to determine causation

• A variable that is purposely manipulated

• Always an error in the study

Why is random assignment important in an experiment?

• It ensures that results will be important.

• It reduces bias and helps establish cause-and-effect relationships.

• It increases sample size.

• It guarantees that each subject receives the same treatment.