# It is also referred to as a probability of committing an incorrect decision about the null hypothesis.

**Question: It is also referred to as a probability of committing an incorrect decision about the null hypothesis.**

In the realm of statistics, the probability of making an incorrect decision regarding the null hypothesis is encapsulated in the concepts of Type I and Type II errors. A Type I error occurs when a true null hypothesis is incorrectly rejected, often considered a false positive. The probability of committing a Type I error is denoted by alpha (α), which is also known as the significance level of the test. Conversely, a Type II error happens when a false null hypothesis is incorrectly accepted, akin to a false negative. The probability of this error is represented by beta (β). These probabilities are crucial in hypothesis testing, as they quantify the risks of drawing incorrect conclusions from data. Researchers aim to minimize these errors by careful study design and choosing appropriate significance levels.

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