Data - Variables Control Chart
overview      

Organize the data for all variables control charts in the same way. Variables charts include:

·    Variables charts for subgroups

·    Variables charts for individuals

·    Time-weighted charts

·    Multivariate charts

Structure your data for these charts using the guidelines below.  

Worksheet Structure

Structure your data down a column or across rows, using the following table as a guide. Multivariate data must be entered down columns, with one column for each variable.

 

 

Subgroups are equal size

Subgroups are unequal size

Univariate (one variable)

Down columns or across rows

Down columns with subgroup indicator column

Multivariate (more than one variable)

Down columns

Down columns with subgroup indicator column

 

Structure subgroup data down a column or across rows. Here is the same data set, with subgroups of size 5, structured both ways. Note that the first five observations in the left data set (subgroup 1) are the first row of the right-side data set, the second 5 observations are the second row, and so on.

 

C1

 

 

40.13

Subgroup 1

39.68

Subgroup 1

40.84

Subgroup 1

41.52

Subgroup 1

 

 

C1

C2

C3

C4

C5

40.02

Subgroup 1

Subgroup 1

40.13

39.68

40.84

41.52

40.02

39.54

Subgroup 2

Subgroup 2

39.54

39.87

40.25

40.47

41.41

39.87

Subgroup 2

 

 

 

 

 

 

40.25

Subgroup 2

 

40.27

Subgroup 2

41.41

Subgroup 2

 

 

When subgroups are of unequal size, you must enter your data in one column, then create a second column of subscripts which serve as subgroup indicators. In the following example, C1 contains the process data and C2 contains subgroup indicators:

 

C1

C2

 

39.68

1

 

40.84

1

Subgroup 1

41.52

1

 

39.54

2

 

39.87

2

 

40.25

2

Subgroup 2

40.47

2

 

41.41

2

 

39.20

3

Subgroup 3

38.72

3

39.39

3

 

Each time a subscript changes in C2, a new subgroup begins in C1. In this example, subgroup 1 has three observations, subgroup 2 has six observations, and so on.

Nonnormal data

To properly interpret Minitab's control charts, you must enter data that approximate a normal distribution. If the data are highly skewed, you may want to use the Box-Cox transformation to induce normality.

You can access the Box-Cox transformation two ways: by using the Box-Cox transformation option provided with the control chart commands, or by using the stand alone Box-Cox command. Use the stand alone command as an exploratory tool to help you determine the best lambda value for the transformation. Then, you can use the transformation option to transform the data at the same time you draw the control chart.

For information on the stand alone Box-Cox transformation command, see Box-Cox Transformation.

For information on the Box-Cox transformation option, see Options -  Box-Cox.

Missing data

See Missing data in control charts for information on how to handle missing data for different types of control charts.