Enter your data for Multiple Correspondence Analysis

Stat > Multivariate > Multiple Correspondence Analysis
  1. Select the option that matches your data:
    • Categorical variables: Select this option if you have raw data. Then enter the columns containing the categorical variables.

      In this worksheet, Gender, Weight, Smokes, and Activity contain the raw data values for each categorical variable.
      C1-T C2-T C3-T C4-T
      Gender Weight Smokes Activity
      Male Normal Yes Yes
      Female Overweight No Yes
      Female Normal No No
      Male Normal No Yes
      Female Underweight No No
      Female Overweight Yes No

    • Indicator variables: Select this option if your data are arranged as indicator variables. Then enter the columns containing the indicators. Each indicator variable (column) represents one level of the categorical variable and each observation (row) takes a binary value depending on whether it does (1) or does not (0) belong to the category. Therefore, the values in all columns must be either 0 or 1.

      In this worksheet, the indicator values correspond with the observations previously shown in the table of raw data. Each worksheet cell contains a 0 or 1 to indicate whether the observation belongs in each category. For example, the first observation in row 1 indicates a male of normal weight who smokes and engages in regular physical activity.
      C1 C2 C3 C4 C5 C6 C7 C8 C9
      Female Male Norm Weight Underweight Overweight No Smokes Smokes No Activity Activity
      0 1 1 0 0 0 1 0 1
      1 0 0 0 1 1 0 0 1
      1 0 1 0 0 1 0 1 0
      0 1 1 0 0 1 0 0 1
      1 0 0 1 0 1 0 1 0
      1 0 0 0 1 0 1 1 0

    Note

    You must delete rows with missing data from the worksheet before using this analysis.

  2. In Category names, you can enter a column of names for the categories to assign the category names. The name column must be a text column whose length matches the number of categories for all categorical variables. For example, suppose you have the following categorical variables: Sex (male, female), Hair color (blond, brown, black), and Age (under 20, from 20 to 50, over 50), and no supplementary variables. To assign category names, you need a column with 2 + 3 + 3 = 8 category names, so the column must contain 8 rows. Minitab displays the first 8 characters of the names in tables, but displays the full name on graphs. If you do not enter category names, Minitab names the columns Column1, Column2, and so on.
  3. In Number of components, enter a number from 1 up to the number of categorical variables. Minitab can create plots with the components that you calculate. To display the column plot, you must have at least 2 components.
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