A Type I error, also known as a false positive, refers to a mistake made in statistical hypothesis testing. It occurs when a null hypothesis, which assumes no relationship or difference between variables, is incorrectly rejected in favor of an alternative hypothesis. In other words, it is a false alarm where researchers mistakenly conclude there is a significant effect or relationship when there is actually none. The probability of committing a Type I error is denoted as α (alpha), which is the level of significance chosen by researchers to set the threshold for rejecting the null hypothesis. A Type I error can lead to erroneous conclusions and can be particularly problematic in scientific research, clinical trials, and legal proceedings, among others.
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