Using Samples to Make Predictions

Using Samples to Make Predictions

Samples

Biased vs. Unbiased

Biased: A non-probability sample is selected based on non-random criteria. For instance, in a convenience sample, participants are selected based on accessibility and availability

Unbiased: Everyone in the population has an equal chance of being selected and represented.

Multiple Choice

A real estate agent surveys people about their housing preferences at an open house for a luxury townhouse.

• Biased Sample

• Unbiased Sample

Multiple Choice

To evaluate the defect rate of its memory chips, an integrated circuit manufacturer tests every 100th chip off the production line.

• Biased Sample

• Unbiased Sample

We can use data from an unbiased sample to make predictions about the population

Example: If 70 out 100 people on 5th avenue like coconut flavored ice cream, how many people in the community (200,000) do you predict like coconut flavored ice cream.

Multiple Choice

Mr. Roy surveyed 60 students to find out their favorite day of the school week. If there are 550 students in the school, predict how many enjoy Fanny Pack Friday the most.

• 283 and 1/3 of a student

• 34

• 283

• 340

Multiple Choice

Jenny randomly selects 20 boxes of crayons from the shelf and finds two boxes with at least one broken crayon. If the shelf holds 130 boxes, how many would you expect to have at least one broken crayon?

• 10 boxes

• 13 boxes

• 6.5 boxes

• 2 boxes

Multiple Choice

Timothy School District surveyed a random sample of 60 middle school students about the amount of time they watch TV. Of the students surveyed, 14 average watching more than 4 hours of TV each day. There are 1143 middle school students in the Timothy School District.

Based on the data, how many students in the whole district watch 4 hours of TV each day?

***Set up two equal proportions to solve!

***Round your answer!

• 14

• 233

• 267

• 876