stages of data analysis to get a look at the data. The chart displays the means at each factor level for every factor.
When do you use Multi Vari Chart
You need one numeric column for the response variable and up to four numeric, text, or date/time factor columns. Each row contains the data for a single observation.
Text categories (factor levels) are processed in alphabetical order by default. If you wish, you can define your own order −see Ordering Text Categories.Minitab automatically omits missing data from the calculations.
Example of a Multi-Vari Chart
You are responsible for evaluating the effects of sintering time on the compressive strength of three different metals. Compressive strength was measured for five specimens for each metal type at each of the sintering times: 100 minutes,150 minutes, and 200 minutes. Before you engage in a full data analysis, you want to view the data to see if there are any visible trends or interactions by creating a multi-vari chart.
1 Open the worksheet SINTER.MTW.
you will see to data ==>
2 Choose Stat > Quality Tools > Multi-Vari Chart.
Response: Enter the column containing the response (measurement) data.
Factor 1: Enter the factor level column.
Factor 2: Enter an additional factor level column.
Factor 3: Enter an additional factor level column.
Factor 4: Enter an additional factor level column.
3. In Response, enter Strength.
4 In Factor 1, enter SinterTime. In Factor 2, enter MetalType. Click OK.
In Factor 1, enter a factor level column.
- If you have more than one factor, enter columns in Factor 2, Factor 3, or Factor 4 as needed.
- If you like, use any dialog box items, then click OK.
The multi-vari chart indicates that an interaction exists between the type of metal and the length of time it is sintered. The greatest compressive strength for Metal Type 1 is obtained by sintering for 100 minutes, for Metal Type 2 sintering for 150 minutes, and for Metal Type 3 sintering for 200 minutes.To quantify this interaction, you could further analyze this data using techniques such as analysis of variance or general linear model.
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