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Results for: Cranksh.MTW MTB > describe c1ĭescriptive Statistics: AtoBDist Variable AtoBDistĠ.4417 3.491 125 0.094 normtest c1 SUBC> rjtest. Retrieving worksheet from file: '\\purple2\resource\wminitab14\Data\Cranksh.MTW' Worksheet was saved on Fri Sep 12 2003 Graph window output - see below! Thus is a Minitab run on the dataset mentioned above. 1Ĭhoose Stat > Basic Statistics > Normality Test. You wish to see if these data follow a normal distribution, so you use Normality test. To ensure production quality,Ī manager took five measurements each working day in a car assembly plant, from September 28 through October 15, and then ten per day from the 18th through the 25th.
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![normal probability plot minitab normal probability plot minitab](https://www.engr.mun.ca/~ggeorge/3423/Minitab/s06NormPlot/i22tables.jpg)
AtoBDist is the distance (in mm) from the actual (A) position of a point on the crankshaft to a baseline (B) position. In an operating engine, parts of the crankshaft move up and down. See GSAVE for more information on this subcommand. If you save the plot, you can view it later with GVIEW and edit the plot with graph editing tools. Minitab automatically adds the extension MGF to the file name. Unless you specify a file extension or use a graphics format subcommand, Use GSAVE to save the graph in a Minitab Graphics Format (MGF) file. Unless you specify a file extension or use a graphics format subcommand, Minitab automatically adds the extension MGF to the file name. When you omit this subcommand, Minitab displays a default title. Use TITLE to specify a title for the graph. For example, if you are using an -value of 0.10 and the p-value displayed in the Graph window is 0.07, then you would reject the hypothesis of normality at the 0.10 level. The -value (also known as the significance level), is the probability that you will reject the hypothesis of normality when the hypothesis is true. 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