Adjusting Sample Sizes and Rounding

The video tutorial explains how to conduct stratified random sampling in a school setting. It covers the calculation of proportions for different grades, the importance of rounding, and how to balance rounding errors to achieve the desired sample size. The tutorial emphasizes the need for accuracy and careful planning in sampling methods.

What is the main purpose of stratified sampling in the context of the school population?

• To ensure each grade is equally represented.

• To represent each subgroup proportionally.

• To focus only on the largest grade.

• To randomly select students without any criteria.

What is the first step in planning a stratified sample?

• Selecting the largest subgroup

• Calculating the total population

• Identifying the subgroups

• Choosing a random number

When calculating proportions for each subgroup, what tool is essential according to the teacher?

• A calculator

• A ruler

• A compass

• A protractor

How is the percentage of students from each subgroup determined?

• By dividing the number of students in a subgroup by the total population

• By multiplying the total population by a random number

• By guessing the number of students

• By using the number of teachers in each grade

How do you determine the number of students to select from each subgroup?

• By selecting students alphabetically

• By multiplying the subgroup proportion by the desired sample size

• By using a random number generator

• By choosing students based on their grades

Why is it important to note where you round from and to?

• To avoid using a calculator

• To confuse the students

• To make the calculations more complex

• To ensure the total sample size is accurate

What is a potential consequence of incorrect rounding?

• The sample will be more accurate

• The sample size will be incorrect

• The sample will be easier to calculate

• The sample will have more diversity

What might happen if all rounding is done in one direction?

• The sample will be perfectly balanced

• The sample size might be too large or too small

• The sample will have no errors

• The sample size will be exactly as planned

Why might you need to adjust the sample size after rounding?

• To ensure the sample is too large

• To make the sample size smaller

• To avoid using a calculator

• To correct for rounding errors

What should you do if the total sample size is not as expected after rounding?

• Recalculate the entire sample

• Add more students randomly

• Ignore the discrepancy

• Adjust the number of students in the subgroup with the largest rounding error