P-Value as a Benchmark in Experimental Research | Prediction by the Numbers

P-Value as a Benchmark in Experimental Research | Prediction by the Numbers
P-Value as a Benchmark in Experimental Research | Prediction by the Numbers
Description

Learn about the origins and meaning of “p-value,” a statistical measure of probability that has become a benchmark for success in experimental science, in this video from NOVA: Prediction by the Numbers. In the 1920s and 1930s, British scientist Ronald A. Fisher laid out guidelines for designing experiments using statistics and probability to judge results. He proposed that if experimental results were due to chance alone, they would occur less than 5 percent (0.05) of the time. The lower the p-value, the less likely the experimental results were caused by chance. Use this resource to stimulate thinking and questions about the use of statistics and probability to test hypotheses and evaluate experimental results.

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