假設檢驗的概念外文翻譯-其他專業(yè)-在線瀏覽
2025-03-24 07:29本頁面
【正文】 o reject implies that the data are not sufficiently persuasive for us to prefer the alternative hypothesis over the null hypothesis. Hypothesis Tests Statisticians follow a formal process to determine whether to reject a null hypothesis, based on sample data. This process, called hypothesis testing, consists of four steps. (1) State the hypotheses. This involves stating the null and alternative hypotheses. The hypotheses are stated in such a way that they are mutually exclusive. That is, if one is true, the other must be false. (2) Formulate an analysis plan. The analysis plan describes how to use sample data to evaluate the null hypothesis. The evaluation often focuses around a single test statistic. (3) Analyze sample data. Find the value of the test statistic (mean score, proportion, tscore, zscore, etc.) described in the analysis plan. (4) Interpret results. Apply the decision rule described in the analysis plan. If the value of the test statistic is unlikely, based on the null hypothesis, reject the null hypothesis. Decision Errors Two types of errors can result from a hypothesis test. Type I error. A Type I error occurs when the researcher rejects a null hypothesis when it is true. The probability of mitting a Type I error is called the significance level. This probability is also called alpha , and is often denoted by α. Type II error. A Type II error occurs when the researcher fails to re
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