Is 600 an ideal sample size?
600 sample size maximizes your Confidence Level, Confidence Interval, and overall investment.
95% is a typical Confidence Level and tells you how sure you can be in the results. You could repeat the research 100 times and arrive at the same result 95% of the time.
Your Confidence Interval (or c.i.) is a "plus-or-minus" figure helping us understand the "Margin of Error" in a result. Using a c.i. of +/- 4% and 65% of your sample responds to a given question, you would know that by sampling the entire population, between 61% (65% - 4%) and 69% (65% + 4%) would answer the same.
Cost-wise, you can achieve savings with a smaller sample size, like n=400, but your c.i. becomes larger (+/- 5%) and less helpful in discerning statistical differences in data.
You can choose a smaller c.i. of +/- 3% however, your sample size needs to increase significantly to n=1,000 and overall costs increase disproportionately.
Example, a full-service study with a final cost of $30 per complete provides these options:
n = 400. c.i. +/- 5% Cost $12,000
n = 600. c.i. +/- 4% Cost $18,000
n = 1,000. c.i. +/- 3% Cost $30,000
Cost figures are for example only.
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