Marketing Research Calculators from Polaris
Have you ever scrambled to find the formula for significance testing? Or searched through your desk drawers to find that table of sample sizes and margins of error?
Search no more! On our website, Polaris Marketing Research has simple, easy-to-use calculators for the most important formulas you need to design and understand marketing research. On our home page, simply click the Sample Size and Margin of Error Calculator button in the left hand margin.
Or, go to the Resources tab on the top banner. Here�s what you�ll find:
Basic Statistical Testing
To understand the results from any survey, you need two measures: the margin of error and the test for statistically significant differences. If it�s been a while since your last statistics course, you may recall that margin of error is the amount of sampling error one could expect due to just chance, above or below the actual figure obtained in the survey results. And sampling error is the estimated inaccuracy of the results of a study when a sample is used to explain the behavior of the total population.
Marketing research firms and clients also use measures of significant differences to illustrate important findings and to help prove or disprove hypotheses about various marketing decisions. To test for statistically significant differences, we provide calculators for proportions and percentages, means as well as the Chi-Square calculation formula. As a general rule, significance testing should only be conducted on base sizes of thirty or more to be considered statistically relevant!
Sample Size Calculator
When you know how accurate you want your data to be, and you know the size of your target population, then you need to calculate how big a sample you need to draw from that population in order to have survey results that can be projected onto the target population. Polaris Marketing Research has provided an easy-to-use Sample Size Calculator for both proportions (percentages) and means on our website. While we all know that calculating the correct sample size for a project requires more than a formula, we believe that this is a good starting point for developing the optimal sample size appropriate to your project objectives.
Of course, if you want to double-check, a link to the relevant formula is found beneath each of the calculators.
Ideally, data collectors like to have about a 10:1 ratio of viable sample records to achieve the level of desired completes. For instance, if you want 500 completed surveys, you will need about 5,000 accurate sample records to complete 500 surveys (within a reasonable timeframe and budget.)
We can�t solve all of the challenges you face as a marketing researcher, but we hope these help simplify some of your more frequent tasks.
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