Sample Size Calculation Concepts

This video tutorial explains how to calculate the sample size needed to predict a population proportion at a given confidence level and margin of error. It covers two scenarios: one without prior knowledge of a sample proportion and another with known sample proportion. The tutorial emphasizes the importance of using the correct formula, rounding up the sample size, and maintaining accuracy by avoiding premature rounding. It concludes with tips on keeping more decimal places for critical values to ensure precision.

What is the main goal when calculating sample size for predicting a population proportion?

• To calculate the total number of samples

• To determine the exact population size

• To estimate a proportion within a specific margin of error

• To find the average of the population

What is the critical value used for a 95% confidence level?

• 1.64

• 2.33

• 1.96

• 2.58

Which formula is used to calculate sample size without prior knowledge of a sample proportion?

• Sample mean squared divided by critical value

• Critical value times sample mean divided by standard deviation

• Critical value squared times 0.25 divided by margin of error squared

• Standard deviation divided by sample mean

Why is it important not to round numbers until the final answer when calculating sample size?

• To keep the calculations simple

• To avoid errors in the critical value

• To ensure the sample size is not underestimated

• To make the calculation process faster

What is the sample size needed when no prior knowledge is available, given a 95% confidence level and 0.015 margin of error?

• 4267

• 4270

• 4269

• 4268

What additional information is needed to use a different formula for sample size calculation?

• Standard deviation

• Population size

• Sample mean

• Sample proportion

How do you calculate 'q hat' when you know 'p hat'?

• Multiply 'p hat' by 2

• Add 0.5 to 'p hat'

• Divide 'p hat' by 2

• Subtract 'p hat' from 1

What is the sample size needed when 'p hat' is 0.225, given a 95% confidence level and 0.015 margin of error?

• 2976

• 2977

• 2978

• 2979

Why is it important to round up the sample size?

• To ensure the sample size is not underestimated

• To make calculations easier

• To increase the confidence level

• To reduce the margin of error

What is the relationship between 'p hat' and 'q hat'?

• 'p hat' is always greater than 'q hat'

• 'q hat' is always 1 minus 'p hat'

• 'p hat' is always equal to 'q hat'

• 'q hat' is always double 'p hat'