Understanding Statistical Significance
Andrew Gelman clarifies the definition of statistical significance and its limitations. He explains that statistical significance does not guarantee that a result is not due to noise, but rather indicates the probability of observing a pattern as extreme as the one observed if there was nothing going on but noise. Gelman uses the example of coin flipping to illustrate this concept.In this clip
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EconTalk
Andrew Gelman on Social Science, Small Samples, and the Garden of the Forking Paths
Related Questions
I have a question about this episode John Ioannidis on Statistical Significance, Economics, and Replication and this Rethinking Statistical Significance. A researcher is studying mirex contamination in farmed salmon. He first found a 95% confidence interval for the mean concentration to be 0.0834 to 0.0992 parts per million. Later, he rejected the null hypothesis that the mean did not exceed the EPA's recommended safe level of 0.08 ppm based on a P-value of 0.0027. Explain how these two results are consistent, discussing the confidence level, the P-value, and the decision.
How is hypothesis testing used in real life as discussed in the episode Andrew Gelman on Social Science, Small Samples, and the Garden of the Forking Paths and the clip Statistical Significance Explained?
How is hypothesis testing used in real life as discussed in the episode False Discovery Rates and the clip Statistical Significance from the episode "Andrew Gelman on Social Science, Small Samples, and the Garden of the Forking Paths"?