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2025-01-31 07:29本頁面
【正文】 ere are two types of statistical hypotheses. Null hypothesis. The null hypothesis, denoted by H0, is usually the hypothesis that sample observations result purely from chance. Alternative hypothesis. The alternative hypothesis, denoted by H1 or Ha, is the hypothesis that sample observations are influenced by some nonrandom cause. Because For example, suppose we wanted to determine whether a coin was fair and balanced. A null hypothesis might be that half the flips would result in Heads and half, in Tails. The alternative hypothesis might be that the number of Heads and Tails would be very different. Symbolically, these hypotheses would be expressed as H0: P = Ha: P ≠ Suppose we flipped the coin 50 times, resulting in 40 Heads and 10 Tails. Given this result, we would be inclined to reject the null hypothesis. We would conclude, based on the evidence, that the coin was probably not fair and balanced. Can we accept the null hypothesis ? Some researchers say that a hypotheis test can have one of two outes: you accept the null hypothesis or you reject the null hypothesis. Many statisticians, however, take issue with the notion of “accepting the null 畢業(yè)設(shè)計（論文）外文文獻(xiàn)翻譯 5 hypothesis.” Instead, the say: you reject the null hypothesis or you fail to reject the null hypothesis. Why the distinction between “acceptance” and “failure to reject?” Acceptance implies that the null hypothesis is true. Failure t
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