Should Market Research Still Be Using Significance Testing?
Over the last few years there have been many calls for market researchers to stop using significance testing based on assumptions of random probability testing to measure the potential impact of sampling error. For example, Annie Pettit writing in The Huffington Post asked “Stop Asking for Margin of Error in Polling Research”. But, despite the concerns about the correctness of using this technique, it seems to still be in common use. In this post, I briefly explain what significance testing is (experts can jump this bit), why it doesn’t do what people seem to think it should do, and the way I think we should be using it in the future. What Is Significance Testing? The type of testing I am talking about in this post relates to sampling error. In quantitative research, a sample is taken from a population and one or more statistics are calculated. These statistics are then used to estimate the values for the total population. For example, assume 1000 people are selected at random from a population of 20 million. Assume that 50% of the sample are female. The inference from this study is that it would be expected that 50% of the total population […]