You cannot conclude that the data do not follow a normal distribution. Supplement 2 Median Rank adjustment for SUSPENDED TEST ITEMS. Supplement 1 Further Details of Weibull Probability plotting. D2 Nonparametric Methods for Probability Plotting. Because the p-value is 0.463, which is greater than the significance level of 0.05, the decision is to fail to reject the null hypothesis. To create a probability plot, choose Graph > Probability Plot and double click on a variable to enter it into the Variables box. D NONPARAMETRIC METHODS AND PROBABILITY PLOTTING. In these results, the null hypothesis states that the data follow a normal distribution. However, you cannot conclude that the data do follow the distribution.įor information on how to specify different distributions and parameters for the test, go to Fitted distribution lines. In Minitab, choose Graph > Probability Plot > Multiple. P-value > α: Cannot conclude the data do not follow the distribution (Fail to reject H 0) If the p-value is larger than the significance level, the decision is to fail to reject the null hypothesis because you do not have enough evidence to conclude that your data do not follow the distribution. Calculations - Calc > Probability Distributions Normal Standardized Scores - Calc > Standardize Evaluating Normality - Graph > Probability Plot. To check the normality of each group of data, a common strategy is to display probability plots. P-value ≤ α: The data do not follow the distribution (Reject H 0) If the p-value is less than or equal to the significance level, the decision is to reject the null hypothesis and conclude that your data do not follow the distribution. We introduced the Pearsons correlation coefficient (or Pearsons r) in Section 2.4.1 as a measure of linear dependence between two variables. An significance level of 0.05 indicates that the risk of concluding the data do not follow the distribution-when, actually, the data do follow the distribution-is 5%. The probability plot correlation coefficient (PPCC) is the Pearsons correlation coefficient of the data plotted in the QQ plot. Usually, a significance level (denoted as α or alpha) of 0.05 works well. ![]() To determine whether the data follow the distribution, compare the p-value to the significance level.
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