![]() When your -value is larger than the p-value displayed with the graph, you should reject the hypothesis of normality. Use RJTEST to perform a RyanJoiner test, which is a correlation based test use KSTEST to perform a Kolmogorov-Smirnov test, which is a chi-square based test. By default, Minitab uses the AndersonDarling test, which is an ECDF based test. There are 3 types of goodness-of-fit test: a chi-square based test, an ECDF based test, and a correlation based test. Use DVALUE to show the percents at the reference x-scale positions. Minitab draws a vertical reference line where the horizontal reference line intersects the line fit to the data, and marks this line with the estimated data value. Minitab marks each percent in the column with a horizontal reference line on the plot, and marks each line with the percent value. The values must be between 0 and 100 when percents are used as the y-scale type or 0 to 1 when probability is the yscale type. You can also use a Ryan-Joiner test (similar to a Shapiro-Wilk test) or a KolmogorovSmirnov test. By default, an Anderson-Darling test for normality is performed and the numerical results are displayed with the graph. The line forms an estimate of the cumulative distribution function for the population from which data are drawn. The grid on the graph resembles the grids found on normal probability paper. Normal plots use the values in the input column as x-values. Saves the graph in a Minitab Graphics Format (MGF) file Specifies the Kolmogorov-Smirnov goodness-of-fit test Specifies the Ryan-Joiner test (similar to Shapiro-Wilk test) ![]() Shows the percents at the reference x-scale positions Stat > Basic Statistics > Normality Test or Graph > Probability Plot Command Syntax NORMTEST C Minitab material on test for Normality NORMTEST example
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |