Data Visualizations

Main areas

1: Column selector panel

A list of the columns in the active worksheet.

2: Source data panel

The available input fields and any display options associated with the selected graph.

3: Candidates list

The complete list of all available graphs.

4: Canvas

The area where Minitab displays the graph previews.

Tips

Continuous variables

Enter one or more numeric columns that you want to graph.

Group variable

Enter a variable that defines the groups. Group labels are shown in the graph legend.

Y-scale

Continuous variables

Enter one or more numeric columns that you want to graph.

Group variable

Enter a variable that defines the groups. Group labels are shown in the graph legend.

Distribution

Continuous variables

Enter one or more numeric columns that you want to graph.

Categorical variables (optional)

Enter up to five columns of categorical data that define the groups. The first variable is the outermost on the scale and the last variable is the innermost.

Whiskers and outliers

Custom percentiles

With large data sets, where outliers are common, you can display custom percentiles instead of outliers to gather more information about the data. Custom percentiles occur outside of the interquartile box and typically occur in the tails of the distribution. In addition, lines are placed at the minimum and maximum values. By default, these percentile values are 0.5, 2.5, 10, 90, 97.5, and 99.5, but you can add, delete, or change them.

Y-scale

Variable display order

Minitab uses the terms "innermost" and "outermost" to indicate the relative position of the scales for multiple levels of groups displayed on a graph. For a horizontal scale, outermost refers to the scale at the bottom of the graph, and innermost refers to the scale farthest from the bottom, closest to the horizontal axis. For a vertical scale, outermost refers to the scale to the far left, and innermost refers to the scale closest to the vertical axis.

Continuous variables

Enter one or more numeric columns that you want to graph.

Categorical variables (optional)

Enter up to five columns of categorical data that define the groups. The first variable is the outermost on the scale and the last variable is the innermost.

Confidence interval

Specify the settings for the confidence interval.

Confidence level

Enter the level of confidence for the confidence interval. Usually, a confidence level of 95% works well. A 95% confidence level indicates that, if you take 100 random samples from the population, the confidence intervals for approximately 95 of the samples will contain the population parameter.

For a given set of data, a lower confidence level produces a narrower confidence interval, and a higher confidence level produces a wider confidence interval. The width of the interval also tends to decrease with larger sample sizes. Therefore, you may want to use a confidence level other than 95%, depending on your sample size.

• If your sample size is small, a 95% confidence interval may be too wide to be useful. Using a lower confidence level, such as 90%, produces a narrower interval. However, the likelihood that the interval contains the population mean decreases.
• If your sample size is large, consider using a higher confidence level, such as 99%. With a large sample, a 99% confidence level may still produce a reasonably narrow interval, while also increasing the likelihood that the interval contains the population mean.

Use Bonferroni method

Method for controlling the simultaneous confidence level for an entire set of confidence intervals. It is important to consider the simultaneous confidence level when you examine multiple confidence intervals because your chances that at least one of the confidence intervals does not contain the population parameter is greater for a set of intervals than for any single interval. To counter this higher error rate, the Bonferroni method adjusts the confidence level for each individual interval so that the resulting simultaneous confidence level is equal to the value you specify.

Two-sided

Use a two-sided confidence interval to estimate both likely lower and upper values for the mean.

Upper one-sided

Use a lower confidence bound to estimate a likely lower value for the mean.

Lower one-sided

Use an upper confidence bound to estimate a likely higher value for the mean.

Use pooled standard deviation

Select when you can assume all populations have equal variances.

Y-scale

Variable display order

Minitab uses the terms "innermost" and "outermost" to indicate the relative position of the scales for multiple levels of groups displayed on a graph. For a horizontal scale, outermost refers to the scale at the bottom of the graph, and innermost refers to the scale farthest from the bottom, closest to the horizontal axis. For a vertical scale, outermost refers to the scale to the far left, and innermost refers to the scale closest to the vertical axis.

Choose one of the following options when you have multiple Y variables with groups.

Categorical variables first, Y's below

Graph variables are the outermost groups and the categorical variables are the innermost groups.

Y's first, categorical variables below

Graph variables are the innermost groups and the categorical variables are the outermost groups.

Continuous variables

Enter one or more numeric columns that you want to graph.

Categorical variables (optional)

Enter up to five columns of categorical data that define the groups.

Jitter individual symbols

If you have identical data values on your graph, individual symbols could hide behind each other. Choose this option to move symbols slightly to reveal overlapping points.

Y-scale

Variable display order

Minitab uses the terms "innermost" and "outermost" to indicate the relative position of the scales for multiple levels of groups displayed on a graph. For a horizontal scale, outermost refers to the scale at the bottom of the graph, and innermost refers to the scale farthest from the bottom, closest to the horizontal axis. For a vertical scale, outermost refers to the scale to the far left, and innermost refers to the scale closest to the vertical axis.

Summarized variable

Enter a column that defines the points in the line chart.

From Function, select the function of the Summarized variable. For example, if you select Maximum, Minitab defines the color for the graph based on the maximum value of the summarized variables. If you enter a text column in Summarized variable, you can only select Percent equal to specified values, Number of nonmissing values, or Number of missing values.

Categorical variable

Enter a categorical variable that defines the x axis.

Legend groups

When you enter multiple Summarized variable, multiple summarized variables are overlaid on the same graph. Select Categories from legend groups to have the groups of the Continuous variable form the legend and the columns you specify in Summarized variable form the x-axis. Select Summarized variables form legend groups to have the columns you specify in Summarized variable form the legend and the groups of the Continuous variable form the x-axis.

Group variable

Enter a variable that defines the groups. Group labels are shown in the graph legend.

Display symbols

Select to display a symbol at each point on the x-axis. If you do not select this option, the graph displays only the lines.

Display function as percent of total

Select this option to change the Y-scale type to percent.

Defects or attribute data

Enter the column that contains the raw data or the summary data. If you have a single column of raw data, enter that column. If you have summary data, enter the column that contains the names of the defects.

If you use text data, be sure that the defect names are distinct within the first 15 characters.

Summarized variable (optional)

Enter a numeric column that contains the counts of the summary data.

Combine the remaining defects after this cumulative percent

Minitab generates bars for defect categories until the cumulative percentage surpasses the percentage that you specify. Then, Minitab groups the remaining defects into a category labeled "Other".

Display percent scale and cumulative line

Select this option to display the cumulative percent symbols, the connecting line, and the percent scale.

Categorical variables

Enter one or more numeric columns that you want to graph.

Summarized variables (optional)

Enter a numeric or text column that defines the bars in the bar chart.

Function

From Function, select the function of the Summarized variables. For example, if you select Maximum, Minitab defines the color for the bar chart based on the maximum value of the summarized variables in each bar. If you enter a text column in Summarized variables, you can only select Percent equal to specified values, Number of nonmissing values, or Number of missing values.

Overlay

When you select multiple categorical variables and you choose to overlay the graphs, you can choose how to display the overlaid bars.

Overlaid with evenly spaced bars

By default, Minitab displays the bars evenly along the axis. Categorical groups are displayed at different levels along the axis in the order in which they appear in Categorical variables.

Overlaid with clustered bars

Minitab displays categorical groups as clustered bars and includes a legend. You can change the grouping by reordering the variables in Categorical variables, or you can choose a different variable from Cluster variable.

Overlaid with stacked bars

Minitab displays the categorical groups as stacked bars and includes a legend. You can change the levels at which the categories appear by reordering the variables in Categorical variables, or you can choose a different variable from Cluster variable.

Note

When you have more than one summarized variable and you choose to overlay the graphs, you have the option to cluster or stack the bars by the summarized variables.

Clustered by summarized variables

Stacked by summarized variables

Order bars by

Display counts as percent of total

When you do not enter Summarized variables, select this option to change the Y-scale type from count to percent.

Display function as percent of total

When you enter Summarized variables, select this option to change the Y-scale type to percent.

Same Y-scale

Make the Y-scale the same across multiple graphs.

Variable display order

Minitab uses the terms "innermost" and "outermost" to indicate the relative position of the scales for multiple levels of groups displayed on a graph. For a horizontal scale, outermost refers to the scale at the bottom of the graph, and innermost refers to the scale farthest from the bottom, closest to the horizontal axis. For a vertical scale, outermost refers to the scale to the far left, and innermost refers to the scale closest to the vertical axis.

Categorical variables

Enter one or more columns of categorical data that you want to graph.

Summarized variables (optional)

Enter one or more columns of summary values that you want to graph.

Display Type

Order slices by

Combine slices of this percent or less

Enter a minimum percentage for separate slices. Categories less than this percentage are grouped into a slice named Other.

Variables

You can graph the x and y-variables as individual pairs or you can graph every combination of the x-y variables. The y-variable is the variable that you want to explain or predict. The x-variable is a corresponding variable that might explain or predict changes in the y-variable. All columns must be numeric, and each x-y variable pair must have the same number of rows.

First, choose one of the following options.

Each Y versus each X

Select to display a separate graph for each possible combination of x and y-variables that you enter.

XY Pairs

Select to display a separate graph for each pair of x and y-variables that you enter. Each x-y variable pair must have the same number of rows.

Then, enter the variables.

Y variables

Select the variables that you want to explain or predict.

X variables

Select the variables that might explain or predict the changes in the Y variables.

Group variable

Enter a variable that defines the groups. Group labels are shown in the graph legend.

Log transformation

Variables

The y-variable is the variable that you want to explain or predict. The x-variable is a corresponding variable that might explain or predict changes in the y-variable. All columns must be numeric, and each x-y variable pair must have the same number of rows.

Y variables

Select the variables that you want to explain or predict.

X variables

Select the variables that might explain or predict the changes in the Y variables.

Gradient defined by mean

Select to define the gradient scale by the value of a third variable.

Gradient Type

Select the color scale for the bins.

Diverging

Bins with high values are red, and bins with low values are blue. In Gradient symmetric around value, enter a value to center the gradient scale at a specific value rather than the center of the frequency of the binned data.

Sequential from low to high

Bins with high values are dark blue, and bins with low values are light blue and light gray. You can use this option to highlight bins with more productivity or to maximize revenue.

Sequential from high to low

Bins with low values are dark blue, and bins with high values are light blue and light gray. You can use this option to highlight bins with low defect rates or to minimize cost.

Log transformation

Variables

The y-variable is the variable that you want to explain or predict. The x-variable is a corresponding variable that might explain or predict changes in the y-variable. All columns must be numeric, and each x-y variable pair must have the same number of rows.

Y variables

Select the variables that you want to explain or predict.

X variables

Select the variables that might explain or predict the changes in the Y variables.

Bubble Size

Enter a column that determines the size (area) of the bubbles.

Layout

Choose a layout option.

Separate graphs for each XY pair

Creates a separate scatterplot for each XY pair.

Overlay XY pairs

Each XY pair is overlaid on a single scatterplot.

Group variable

Enter a variable that defines the groups. Group labels are shown in the graph legend.

Log transformation

Matrix of Plots

In Continuous variables, enter columns of numeric data with the same number of rows. Minitab displays a scatterplot for each combination of variables.

In this worksheet, Rate of Return, Sales, and Years are the graph variables. The graph shows the relationships between each possible combination of graph variables.

C1	C2	C3
Rate of Return	Sales	Years
15.4	50400200	18
11.3	42100650	15
9.9	39440420	12
...	...	...

Each Y versus each X

In Y variables, enter columns of numeric data that you want to explain or predict. In X variables, enter columns of numeric data that might explain changes in the Y variables.

In this worksheet, Rate of Return and Sales are the Y variables and Years is the X variable. The graph shows the relationships between each Y variable and the X variable.

C1	C2	C3
Rate of Return	Sales	Years
15.4	50400200	18
11.3	42100650	15
9.9	39440420	12
...	...	...

Layout

Select Full matrix to display both the lower left portion of the matrix and the upper right portion. The two portions display the same data with the axes reversed. For example, variables that appear on the x-axis in the lower left portion of the matrix appear on the y-axis in the upper right portion.

Full matrix

Lower left

Upper right

Group variable

Enter a variable that defines the groups. Groups are represented by different colors and symbols. For example, the following matrix plot shows the relationships between each possible combination of the variables Rate of Return, Sales and Years, divided into three groups.

Variable label placement

Select Diagonal to display the axes labels along the diagonal of the matrix plots. Select Boundary to display the axes labels along the border of the matrix.

Diagonal

Boundary

Scale

Use the same scale across multiple graphs.

Same Y-scale

Use the same Y-scale across all graphs.

Same X-scale

Use the same X-scale across all graphs.

Continuous variables

Enter the columns that contain the data. You must enter at least two columns of numeric data. Each column must have the same number of rows.

Gradient Type

Select the color scale for the bins.

Automatic

When you select Automatic, the gradient type depends on the calculation of the Pearson correlation coefficients.

• If the coefficients are positive and negative, the Gradient Type is Diverging symmetric around 0.
• If the coefficients are all positive, the Gradient Type is Sequential from low to high.
• If the coefficients are all negative, the Gradient Type is Sequential from high to low.

Diverging

Bins with high values are red, and bins with low values are blue. In Gradient symmetric around value, enter a value to center the gradient scale at a specific value rather than the center of the frequency of the binned data.

Sequential from low to high

Bins with high values are dark blue, and bins with low values are light blue and light gray. You can use this option to highlight bins with more productivity or to maximize revenue.

Sequential from high to low

Bins with low values are dark blue, and bins with high values are light blue and light gray. You can use this option to highlight bins with low defect rates or to minimize cost.

Display correlation values

Select to display the value of the Pearson correlation coefficient within each rectangle of the graph.

Variables

Enter at least two columns of numeric data.

Row labels

Enter a column that contains labels for each series. Minitab uses this column to label a series on the plot when you hover over it with your cursor. If you don't enter a Group variable Minitab uses the label column to create a legend for the parallel plot.

Layout

Choose one of the following layout options.

Individual series

Creates a parallel plot that displays a series for every row in the worksheet. The worksheet must include at least two columns of numeric data.

Individual series by group

Creates a parallel plot that displays a series for every row in the worksheet and uses the same color for each level of the grouping variable. The worksheet must include at least two columns of numeric data and one column that contains the groups.

Summarized groups

Creates a parallel plot that displays the mean of each series for every group in the worksheet, not every row. The worksheet must include at least two columns of numeric data and one column that contains the groups.

Group variable

Enter a variable that defines the groups. Group labels are shown in the graph legend. You must enter a column when you select Individual series by group or Summarized groups.

Y-scale

Select how you want to display the y-scale.

Percent of range

Select to plot each variable with a unique y-scale. A series that contains all of the minimum or maximum values for each variable will be a horizontal

line.

Standard units

Select to plot each variable with a unique y-scale. The minimum and maximum values for each scale are the overall minimum and maximum z-score values from all the data that you entered converted to each variable's scale.

For example, the first variable's maximum value has a z-score of 2, while the other two variable's maximum value has a z-score of 1. The maximum value for each variable's y-scale is the value that corresponds to a z-score of 2.

Original data

Select to use a single y-scale that is repeated for each variable. The minimum and maximum values for the scale are the overall minimum and maximum values from all the data that you entered.

Sort variables from greatest to least variation in lines

If you select Standard units or Original data, you can sort the variables based on the variation. This can be useful when you have many variables and you want to see which one separates the series the most. If you do not select this option, Minitab sorts the columns in the same order as you enter them in the Variables dialog box.

Unsorted

Sorted

Categorical row variables

Enter up to five columns where the categories are represented as rows on the heatmap.

Categorical column variables

Enter up to five columns where the categories are represented as columns on the heatmap.

Summarized variables (optional)

Enter a numeric or text column that defines the color gradient of the rectangles in the heatmap. If you enter multiple columns, Minitab generates a separate heatmap for each variable that you enter.

Function

From Function, select the function of the Summarized variables. For example, if you select Maximum, Minitab defines the color gradient for the heatmap based on the maximum value of the summarized variables in each rectangle. If you enter a text column in Summarized variables, you can only select Percent equal to specified values, Number of nonmissing values, or Number of missing values.

Gradient Type

Variables

For more information on table layouts, go to Arrangement of output tables.

In this worksheet, Strength is the summarized variable and contains fiber strength measurements. Machine is the column variable and indicates the machine that produced the fiber. Operator is the row variable and indicates the person operating the machine.

C1	C2	C3
Strength	Machine	Operator
38	1	1
40	2	2
63	3	3
59	4	1
76	1	2
...	...	...

Categorical Variable Summary Statistics

Display Options

Continuous variables

Enter one or more columns of time-ordered numeric data that you want to graph.

Time scale labels (optional)

Label the x-axis with values from a column that contain date/time, numeric, or text values for the scale. For example, on the following time series plot, the column specifies the shift and day.

C1-T
Shift and Day
S1D1
S2D1
S3D1
...

Layout

Set the following layout options.

Panel continuous variables

Columns in the Continuous variables input field appear on a single time series plot where all variables share a single X-axis and each continuous variable appears in its own panel.

Overlay continuous variables

Columns in the Continuous variables input field are overlaid on a single time series plot.

Y-scale

Select how you want to display the y-scale.

Original data

Select to use a single y-scale that is repeated for each variable. The minimum and maximum values for the scale are the overall minimum and maximum values from all the data that you entered.

Percent of range

Select to plot each variable with a unique y-scale. A series that contains all of the minimum or maximum values for each variable will be a horizontal line.

Log scale

A logarithmic scale linearizes logarithmic relationships by changing the axis, so that the same distance represents different changes in value across the scale. This option is available only for positive data.

Continuous variables

Enter one or more columns of time-ordered numeric data that you want to graph.

Time scale labels (optional)

Label the x-axis with values from a column that contain date/time, numeric, or text values for the scale. For example, on the following time series plot, the column specifies the shift and day.

C1-T
Shift and Day
S1D1
S2D1
S3D1
...

Stacking order

You can change the order in which variables are stacked when you create the graph.

Order of entry (first on top)

Stack the variables in the order in which you enter them in the dialog box. The first variable you enter is on the top, the second variable is under the first, and so on.

Degree of variation (largest on top)

Stack the variables by the degree of variation. The variable with the largest variation is on the top, the variable with the second largest variation is under the first, and so on.

Log transformation: Y-scale

Select to transform the Y-scale using logarithm base 10. A logarithmic scale linearizes logarithmic relationships by changing the axis, so that the same distance represents different changes in value across the scale. These options are available only for positive data.