Sample size and population are some of the most important aspects of creating a survey. These two pieces of data can significantly influence the results and the information learned from your population. If you do not have enough people in your survey, are you really getting an entire picture of the population as a whole? If you have a population in the entire city that you are working with – and you only survey the students in your local college – you may find that this is not indicative of your target market. So how do you fix this issue?
Figuring out the best ways to evaluate the population and sample size is key to being able to get a full picture of the target market, who you are trying to reach, and the population as a whole. Make sure you calculate the ideal population and sample size for your survey so you can gain the right insight into your world, figure out more about your marketing strategy, and get a full picture of those you are trying to reach.
First off – what is the sample size? The sample size is simply the number of respondents in the survey who are specifically chosen by the researcher to get an overview of the population as a whole. You need to choose a sample size that is indicative of the entire population – if you are trying to get a survey of the entire female student-athlete population in the university, then make sure your sample size fits your study criteria. Furthermore, make sure the sample size is not too large – a big sample size can cause you to waste your time, whereas one that is too small can cause you to not gain enough information from your findings.
So how do you calculate the correct population and sample size? There are two measures you have to keep in mind when it comes to your survey – margin of error and confidence level.
- The margin of error – the margin of error with your study is the amount of deviation – or the difference – that you are allowed to have with your survey results. For example, if you find that you’re right with your survey 97 out of 100 times, then this is a 97% margin of error. You try to keep your margin of error above 90% when you are conducting surveys, to show the validity and the reliability of your methods.
- Confidence level – The second measure that you should use for your survey to be reliable and consistent is the confidence level. This Is the measure of how often your survey actually lines within the margin of error – if your margin of error is 95%, you may find that your confidence falls at 95% “X” number of times.
Now that you know the measure of what influences your population and sample size, you need to know – how many people do you need for your survey? Typically you will find that you can use the margin of error and confidence level to calculate the total number of survey participation and the sample size that is required for higher accuracy.
Furthermore, take into account the response rate – the response rate is the number of respondents who actually complete the survey questionnaire compared to the number of surveys that you distributed. Try to keep the response rate as high as possible so you can gain more data based on the amount of effort you spend on your survey distribution efforts.
Typically, with the popularity and sample size, you will find that these two measures of your survey are indulged by the margin of error and confidence level. Since you are going to be choosing the sample size and population-based on how accurate you need your survey to be, try to keep the confidence level above 95% and the margin of error less than 5% – this way, you can ensure that your survey is almost always accurate no matter how many times you conduct this survey repeatedly. Focusing on the margin of error, confidence level, and the sample size is key to being able to gain accurate results by repeatedly conducting the survey of your desired population.