Hypothesis testing is one of the most widely used procedures in statistical decision making. However, it can result in several errors. This entry focuses on the Type I error, which occurs when a true hypothesis is wrongly rejected.
Type I errors occur in statistics when hypothesis tests are used to make statistical decisions based on experimental data. In this decision process, a simple statement or null hypothesis is formulated on the true status of an unobserved phenomenon. At the same time, an alternative hypothesis is defined to reflect the opposite situation. For instance, a new drug is tested for its capacity to reduce high blood pressure. The null hypothesis states that the new drug does not change blood pressure. Any differences that are observed are ...
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