In statistics, a p-value is a measure of the strength of evidence against the null hypothesis. It indicates the probability of observing the observed data, or more extreme results, if the null hypothesis were true. A low p-value (typically below a predefined significance level, often denoted as α) suggests that the observed data are unlikely under the null hypothesis, leading to its rejection. Conversely, a high p-value indicates that the observed data are consistent with the null hypothesis, and it fails to provide sufficient evidence to reject it.
How likely are your results due to chance?
P-Values measure the statistical significance of your findings. 📉📊 #PValues #Statistics #Research #MentalModels
#DataScience #EvidenceBased #CriticalThinking
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