A good statistical sample size is at least 100, and preferably more, participants. With a 100-participant sample size, the researcher has a margin of error of approximately 10 percent with a 95 percent confidence rating in the results. For the researcher to increase his confidence rating and reduce his margin of error he has to increase the size of the sample.

The more the sample size increases, the more the margin of error decreases. This is because by surveying a larger sample of people, the researcher is more likely to receive results that complement the viewpoint of the general population. By utilizing a smaller sample size, the researcher is skewing his results by basing them on the statistics given to him by a small percent of the population. The researcher's confidence rating is his guide to the probability of how accurate his research is. Most researchers utilize a 95 percent correct confidence level when conducting statistical research. An example is if the researcher surveys 500 people, his margin of error is 4.5 percent with a 95 percent confidence level. This means if 50 percent of the surveyed people choose A instead of B, the researcher can say with 95 percent confidence that between 45.5 percent and 55.5 percent of the population prefer A over B.

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When the **sample** **size** increases, the chances of getting an error (margin of error) in a percentage or mean becomes smaller. This means that the **statistical** results ...