Hypothesis_Testing(统计学假设检验).ppt

* * * * * * * When reading a scientific journal, you typically will not be told explicitly that the researcher evaluated the data using a z-score as a test statistic with an alpha level of .05. Nor will you be told that “the null hypothesis is rejected.” Instead, you will see a statement such as: The treatment with medication had a significant effect on people’s depression scores, z = 3.85, p .05. Let us examine this statement piece by piece. First, what is meant by the term significant? In statistical tests, this word indicates that the result is different from what would be expected due to chance. A significant result means that the null hypothesis has been rejected. That is, the data are significant because the sample mean falls in the critical region and is not what we would have expected to obtain if H0 were true. Next, what is the meaning of z = 3.85? The z indicates that a z-score was used as the test statistic to evaluate the sample data and that its value is 3.85. * Finally, what is meant by p .05? This part of the statement is a conventional way of specifying the alpha level that was used for the hypothesis test. More specifically, we are being told that an outcome as extreme as the result of the experiment would occur by chance with a probability (p) that is less than .05 (alpha) if H0 were true. * In circumstances where the statistical decision is to fail to reject H0, the report might state that There was no evidence that the medication had an effect on depression scores, z=1.30, p .05. In this case, we are saying that the obtained result, z= 1.30, is not unusual (not in the critical region) and is relatively likely to occur by chance (the probability is greater than .05). Thus, H0 was not rejected. Using the p-Value in Hypothesis Testing If the p-Value ? a, H0 cannot be rejected. If the p-Value a, H0 is rejected. p-value does not only tell us whether we should reject H0, but also tell us how confident we are to reject it. * Sample means that