Sampling and Mean Estimation Concepts

The video covers Math 7 Unit 8 Lesson 17 on sampling variability. It explains the concept of sampling variability, the importance of calculating means from different samples, and how larger sample sizes lead to more accurate population means. Activities include analyzing reaction times and TV show samples. The lesson concludes with a summary and homework discussion.

What is the main goal when taking multiple samples from a population?

• To ensure all samples are identical

• To find the largest sample mean

• To get a mean closer to the population mean

• To reduce the number of samples needed

Why might two different samples from the same population have different means?

• Due to random selection of different individuals

• Because they are taken at different times

• Due to errors in calculation

• Because one sample is larger than the other

In the activity with TV show viewers, what was the purpose of using 100 samples?

• To confuse the students

• To ensure all samples have the same mean

• To reduce the number of samples needed

• To better estimate the population mean

What does a dot plot help you estimate in the context of sampling?

• The population mean

• The exact number of samples

• The mode of the samples

• The median of the samples

How does increasing the sample size affect the sample mean?

• It increases the variability of the sample mean

• It makes the sample mean less accurate

• It makes the sample mean closer to the population mean

• It has no effect on the sample mean

What was the estimated mean distance baseball fans were willing to travel?

• 64 miles

• 80 miles

• 50 miles

• 70 miles

In the school concert example, what was the mean age of the population?

• 30 years

• 35 years

• 45 years

• 40 years

What should Elena do to increase the likelihood of her sample mean being within one year of the population mean?

• Select a smaller sample size

• Select a larger sample size

• Use the same sample size

• Select samples from a different population

What is the probability of the hockey team winning a game in the simulation?

• 75%

• 100%

• 25%

• 50%

In the hockey team simulation, what does a successful outcome represent?

• A loss in the game

• A draw in the game

• A win in the game

• A postponed game