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How to collect a simple random sample

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It’s nearly impossible to get insights from your entire group of consumers, which is why random sampling is a good way to tap into those insights. Simple random samples are a subset of individuals that is representative of the whole group. Read on to find out more about simple random samples and the steps needed to collect yours.

A simple random sample is a type of probability sampling method used in market research and other types of studies. Simple random sampling selects a small subset from a larger group of participants. The technique provides each person from the larger population with an equal and fair chance of being selected for the smaller group. This is just one of several types of sampling for market research.

Using the simple random sampling process ensures that your small sample group will be representative of the total population—and free from researcher bias. For example, if a business owner with a large corporate office is studying the effects of employees working from home, his belief that he needs people to inhabit the space could prompt him to choose a sampling of people who are like-minded. This research bias would influence the results and skew them towards his desired outcome of having his employees in the office. Simple random samples prevent bias from influencing the results.

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SurveyMonkey Audience makes simple random sampling even simpler. The tool ensures high-quality results easily, quickly, and on-demand. If you don’t have the contact details or the number of participants for the population you want to survey, give SurveyMonkey Audience a try. Once you have your sample selected and you send your survey, your data will be collected in a customizable dashboard for easy analysis and sharing.

There are some definite advantages to using simple random samples:

  • Your data set is unaffected by researcher bias
  • All members of your larger population have an equal and fair chance of being selected
  • Data represents the larger population, so no segmenting is needed to refine results
  • Generalized results provide accurate information for sweeping decisions
  • It’s fast and easy to complete
  • No technical knowledge is required

Now that you understand what it is and its advantages, let’s talk about when you should use simple random sampling.

Simple random sampling is used when you need to make generalizations about a specific population without any bias. It works best if you use an online tool like SurveyMonkey for conducting simple random sampling studies, collecting data, and distributing results. You also need access to a complete list of the population you are targeting and a way to contact each person who is selected for the study. SurveyMonkey Audience is very useful in identifying and contacting individuals in your sample. 

Sometimes, simple random sampling isn’t the best method for finding your sample group. Simple random sampling takes its participants randomly from the total population you’ve identified. 

Stratified random sampling, another form of probability sampling, uses subdivisions in the population that need to be accounted for. Each smaller group is identified as strata and an equal number from the strata is randomly selected to ensure all groups are represented. So, if you’re studying the wage gap between gender identities, you’ll need to distinguish between male, female, and those who do not identify as either male or female participants to ensure that they are equally represented within your sample group. 

If simple random sampling is right for your research, use the following steps to collect your simple random sample.

There are four key steps in selecting a simple random sample.

What population do you want to research? Remember, you need to be able to contact each member of the population you choose so that you can collect data from everyone selected for the sample. This, again, is where SurveyMonkey Audience is a lifesaver.

While a larger sample size yields more statistical certainty, it will cost more and take more time. But if your sample size is too small, your data may not be accurate. How do you know what your sample size should be? 

Our sample size calculator will help you determine the appropriate sample size for your survey. If you prefer to do the calculations by hand, the formula is:

Sample size =
 

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

There are two ways to select your sample randomly. Both remove bias from the selection process. Before you begin, prepare a list of the full population you are choosing from, along with their contact information. 

You’ve probably used the lottery method to make selections in other circumstances. You start with a list of names of the people in your full population—ensure that you have contact information for each one.

  1. Print out the names of the people in your population
  2. Cut each name out
  3. Put each individual piece of paper with a name on it into a bowl
  4. Make sure the name papers are well mixed before beginning to make selections
  5. Pull names out at random until you reach your selected sample size
  6. Create a table with the corresponding contact information for each selection for easy reference.

If you prefer, you can use a random number generator—it’s easy to create one in an Excel spreadsheet using the formula =RAND(). Follow these steps to create your simple random sample with Excel:

  1. Enter the names of the customers you have contact information for in the first column
  2. Add a new column to the right and name it Random_number
  3. Make a third column for the email addresses of each customer
  4. In the first row under the heading row, in the Random_number column, enter the formula =RAND()
  5. Press enter and a random number will appear in the selected cell
  6. Select the cell with the new random number in it
  7. Drag the small box at the bottom right corner of the cell and drag the box down the column to the bottom of the list—this generates a new random number for each name on your list
  8. To prevent the numbers from changing as you work with the table:
    1. Highlight all random numbers in the Random_number column
    2. Click copy
    3. Highlight the random numbers again and right-click on them
    4. Click paste special
    5. Click paste values
    6. This removes the random function from the cells
  9. To take a random sample from the list
    1. Highlight the columns with data and numbers in them
    2. Click Home
    3. Click Sort and Filter
    4. Click Custom Sort
    5. Sort by the column with the random numbers
    6. Order smallest to largest
    7. Click OK
  10. Your list has now been randomly sorted, and you can select the first 10 or 200—whatever you need your sample size to be—and that’s the list of your randomized participants.

Once you have your random sample selected, it’s time to collect data. Do your best to ensure that every individual participates in the study, or your findings may be biased because a group is underrepresented in your sample.

Set a due date for individuals to complete your survey. If any do not respond, send an email requesting that they do so. You may need to call to speak to non-responding participants to prompt them to participate. A higher response rate equals more valid results.

Wondering how this looks in practice? Let’s look at some examples of circumstances that use simple random sampling:

  • At a children’s party, teams are chosen for games by putting everyone’s name in a hat and choosing them at random
  • A pharmaceutical company is ready to test the efficacy of a new drug. Volunteers are chosen at random—half receiving the medication and half receiving a placebo
  • The American Community Survey (ACS) is used by the US Census Bureau to follow a random sample of US citizens for a year to draw conclusions about the entire US population

As long as you have a list of your target population and ways to reach them, you can use simple random sampling. If you don’t have a list, SurveyMonkey Audience will help you find your ideal population—customized to your needs. And if you’re not sure what sample size is right for your study, use our sample size calculator. Just plug in your total population, the margin of error, and confidence level. Good luck!

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