Question

You are designing a study to assess the benefit and risk of a new intervention. You want a

sample size to establish the risk of an event in 1 out of 100 persons. How big a sample size per

group do you need? Cite reference or show work.

Answer 1

What is sample size?

Sample size is the number of completed responses your survey receives. It’s called a sample because it only represents part of the group of people (or target population) whose opinions or behavior you care about. For example, one way of sampling is to use a “random sample,” where respondents are chosen entirely by chance from the population at large.

With this definition in mind, let’s dive into the following topics:

• The different ways to interpret your sample’s results
• The formula used to calculate sample size
• Why having an appropriate sample size for a survey matters
• How the significance of sample size varies across survey types

Understanding sample sizes

Here are two key terms you’ll need to understand to calculate your sample size and give it context:

Population size: The total number of people in the group you are trying to study. If you were taking a random sample of people across the U.S., then your population size would be about 317 million. Similarly, if you are surveying your company, the size of the population is the total number of employees.

Margin of error: A percentage that tells you how much you can expect your survey results to reflect the views of the overall population. The smaller the margin of error, the closer you are to having the exact answer at a given confidence level.

Sampling confidence level: A percentage that reveals how confident you can be that the population would select an answer within a certain range. For example, a 95% confidence level means that you can be 95% certain the results lie between x and y numbers.

How to calculate sample size

Wondering how to calculate sample size? If you’d like to do the calculation by hand, use the following formula:

Sample size =

N = population size • e = Margin of error (percentage in decimal form) • z = z-score

The z-score is the number of standard deviations a given proportion is away from the mean. To find the right z-score to use, refer to the table below:

Things to watch for when calculating sample size

• If you want a smaller margin of error, you must have a larger sample size given the same population.
• The higher the sampling confidence level you want to have, the larger your sample size will need to be.

Reference: https://www.surveymonkey.com/mp/sample-size-calculator/