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Select the variable, leave the distribution choiceas "Normal".The graph will print with "confidencebands" around the 45-degree line. Normal probability plots: Use Graph>ProbabilityPlot. The variableto be plotted goes in Y - so the boxplot will be drawn vertically.If several side-by-side boxplots (for categories) are desired,the values must be stacked in one column, with a second columncontaining an index identifying the category from which each valuecomes. Any options you set will remain inplace for your session (until you Exit Minitab) unless youchange them.īoxplots: Use Graph>Boxplot.
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The number of classes or the values for eitherthe midpoints or the cutpoints. Whether the bars arelabeled by the class midpoints or cutpoints (classlimits) 3. the type of histogram (frequency,relative frequency, cumulative, etc.) 2. The Annotationbutton will let you write a title for your histogram. Select thevariable(s) by double-clicking in the list. For information on saving the results, see VI.Saving and printing your work A: The graphs you may want You can also get somewhat clunkygraphs drawn in the Session window (so they print with the sessionwindow) using the Character graphs commands (There is a Character graphs submenu at the bottom of the Graphmenu). Minitab produces two general types of graphs: the standardgraphing commands produce High resolution graphs whichuse graphics drawing methods and appear in special graph windows(but are not attached to the session file - so they have to besaved and printed separately). Questions to answer with the normal probability plot:Īre y values across their range showing an approximate normal distribution?Ĭan tell us if something abnormal happened there.Minitab:Graphs Introduction to MINITAB in the Saint Mary's MicrocomputerLab IV. ( the probability that values smaller than this value occur in a normally distributed data set). Then it uses the normal distribution to calculate the percentile of each value. The Normal Probability Plot: Minitab puts all calculated residuals in order from smallest to largest (“ranks” them). Here blue dots are above and below the line, no matter what the x value is. The latter would indicate that the errors are not normally distributed and not totally random, so they might be influenced by the x value. The Residuals vs Fit Plot answers the questions: Are the errors in the y values (residuals) evenly distributed among all x values? Or are there any sections on the line (or in the data) that show a bigger variation in y? TIP: Look on Blackboard for the following Excel file, which compares all the output options of these tools with the Excel Regression Data Analysis tool:Ĭomparison of Output options Minitab Fitted Line Plot, Fit Regression Model, Excel Regression Tool.xls However, it provides the p values and confidence intervals for the line coefficients, which the Fitted Line Plot doesn’t. The Fit Regression Model tool does not display the fitted line plot. In addition, it generates the fitted line plot, with the data points, the fitted line as well as bands for the confidence interval and the prediction interval. The Fitted Line Plot tool provides options to output all the results needed to evaluate a linear regression. The Fit Regression Model tool is mostly needed for multiple linear regression. Since it has a lot fewer options, it is easier to use. TOOL 2: Select Stat -> Regression -> Fit Regression Modelįor simple (one predictor variable) linear (and quadratic or cubic non-linear) regression, the Fitted Line Plot tool is fully sufficient. Minitab offers two different tools for linear regression: TOOL 1: Select Stat -> Regression -> Fitted Line Plot