Think about the potential size of your target population.
For example, if you're sending a survey to male i Phone users in California, you may need to do some research to determine how many total men fit that criteria.
To calculate the number of respondents you need (known as your sample size), use our sample size calculator. If you need a guaranteed number of respondents, buy survey responses from Survey Monkey Audience.
You specify the number of responses you need and we'll use your targeting criteria to find you respondents.
The following observations need to be taken into account when determining sample size: a) The magnitude of sampling error can be diminished by increasing the sample size.
b) There are greater sample size requirements in survey-based studies than in experimental studies.In non-probability sampling, on the other hand, sampling group members are selected on non-random manner, therefore not each population member has a chance to participate in the study.Non-probability sampling methods include purposive, quota, convenience and snowball sampling methods.Sampling can be explained as a specific principle used to select members of population to be included in the study.It has been rightly noted that “because many populations of interest are too large to work with directly, techniques of statistical sampling have been devised to obtain samples taken from larger populations.”.In other words, due to the large size of target population, researchers have no choice but to study the a number of cases of elements within the population to represent the population and to reach conclusions about the population (see Figure 1 below). Population, sample and individual cases Brown (2006) summarizes the advantages of sampling in the following points: a) Makes the research of any type and size manageable; b) Significantly saves the costs of the research; c) Results in more accurate research findings; d) Provides an opportunity to process the information in a more efficient way; e) Accelerates the speed of primary data collection.The process of sampling in primary data collection involves the following stages: .The number of respondents you need depends on your survey goals and how confident you want to be in your results.The more confident you want to be, the less of a margin of error you should accept.Common standards used by researchers are 90%, 95%, and 99%.A 95% confidence level means if the same survey were to be repeated 100 times under the same conditions, 95 times out of 100 the measure would lie somewhere within the margin of error.