Data considerations for Descriptive Statistics (Tables)

To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.

Collect raw data or frequency data: The raw data for each variable are in separate columns in the worksheet, and each observation is in a separate row. Multiple columns of data must all have the same number of observations.; If you summarize the counts of data, you must have a column of frequencies. For more information, go to Comparison of summarized data, frequency data, and raw data.
You can have quantitative data as well as categorical data: A categorical variable has values that you can put into a countable number of categories or groups. In this analysis, categorical data are used for the table rows and columns.; An associated variable (quantitative variable) has values that you can order, measure, and summarize using summary statistics. For more information, go to Comparison of categorical and quantitative variables.
Missing categorical values are counted, but not included in the calculations: By default, Minitab displays all missing values in your tables, but does not include them in the calculations unless you select Include displayed missing values in calculations in the Options sub-dialog box. When a data point is missing, by default, the entire row (observation) in the worksheet is omitted from the calculation.; For more information, go to How to interpret missing values in a table.