Exploring Populations and Samples

What is the primary difference between a population and a sample?

• A sample is always smaller than a population.

• A population includes all possible outcomes, a sample is a subset.

• A sample is more important than a population.

• There is no difference; both terms mean the same.

Why is a random sample important for unbiased results?

• It is cheaper to obtain.

• It ensures every member has an equal chance of being selected.

• It is quicker to analyze.

• It requires less data.

What is the purpose of using a random sample in surveys?

• To save time and resources.

• To focus only on specific groups.

• To ensure each member has an equal chance of selection.

• To make the survey easier to conduct.

What makes the airline survey biased?

• It surveys only passengers from on-time flights.

• It surveys passengers from all flights.

• It surveys passengers without flights.

• It surveys only passengers from delayed flights.

Why is the newspaper's method of selecting subscribers considered unbiased?

• It selects the oldest subscribers.

• It selects the most active subscribers.

• It selects subscribers randomly.

• It selects only new subscribers.

What is the flaw in the researcher's survey at the movie theater?

• It surveys people at multiple venues.

• It surveys too many people.

• It only surveys people at one type of entertainment venue.

• It includes too many forms of entertainment.

Why is the reporter's conclusion about the most common injury biased?

• She visits multiple hospitals.

• She observes a variety of injuries.

• She only visits during the summer.

• She visits all year round.

What is a common mistake made when collecting data to draw conclusions about a population?

• Surveying an entire population.

• Surveying a random sample.

• Surveying a biased sample.

• Surveying too many people.

How do you use proportions to predict the number of students with cell phones?

• Subtract the sample from total students.

• Add the sample to total students.

• Divide the sample by total students.

• Multiply the sample proportion by total students.

Based on a sample, how many computer chips out of 5,000 are predicted to be defective?

• 500

• 700

• 667

• 600