The scales of a graph determine the reference points for data displayed on the graph. A graph scale includes a vertical or horizontal axis line, tick marks for specific values or categories, and tick labels.
Graphs can have several types of scales, often on the same graph on different axes. A continuous scale is a sequential numeric scale with an infinite number of points between values. A categorical scale displays distinct, related groups of data; the categories are equally spaced and the space between the categories has no meaning.
Other types of scales include time scales, which display equally spaced time units (for example, day, month, quarter, year), and probability or percent scales, which are logarithmic and show the probability or percentage of observations that fall at or below certain values.
When you plot two variables in Minitab, you usually display the y variable on the vertical or y-axis to represent the response and the x variable on the horizontal or x-axis to represent the predictor. When you plot variables in three dimensions, the x and y variables usually represent the predictor variables and the z variable usually represents the response.
Minitab fits the graph scales to the range of your data, but you can change the range.
For probability plots, bar charts, boxplots, interval plots, individual values plots, and histograms, you can transpose the horizontal and vertical scales.
On a scatterplot, time series plot, and area graph, you can transform a continuous scale with a logarithm or power to get a different view of your data.
If you have overlaid scatterplots or time series plots, you can add a secondary scale to display on the opposite side of the graph.
On time series plots, area graphs, and control charts, the x-axis represents chronological time in equally spaced intervals. You can choose the labels to use for the equally spaced time units.
You can change the y-scale type of histograms, probability plots, and empirical CDF plots. For example, by default, the y-scale of a histogram represents frequency (each bar represents the frequency of values within the specified bin), emphasizing the magnitude of each bin. If your audience doesn't have enough process knowledge to understand the frequency values, you can change the graph's y-scale type to recast these frequency values as percentages (each bar represents the percentage of all values within the bin), a format they may find more meaningful.
By default each bar represents the frequency of values within the bin. Change the y-scale type to Percent to make each bar represent the percentage of all values within the bin. Use Density when you want to compare distributions and the sample size differs. Density is also useful when you compare bars and the bin widths are unequal. Density is calculated as the proportion of observations divided by the bin width.