Categorical

Example 1

Summary: Perform response screening analysis to identify most significant categorical factors

Code:

// Open data table
dt = Open("$Sample_Data/Consumer Preferences.jmp");
// Response Screening
Response Screening(
    Y(
        :Job Satisfaction,
        :I am working on my career,
        :I want to see the world,
        :
        My home needs some major improvements,
        :
        I have vast interests outside of work,
        :
        I want to get my debt under control,
        :I come from a large family,
        :Brush, :Floss
    ),
    X(
        :Gender, :Single Status,
        :School Age Children, :Age Group
    ),
    Force X Categorical( 1 ),
    Force Y Categorical( 1 )
);

Example 2

Summary: Perform categorical analysis with crosstab transposed and test for response homogeneity

Code:

// Open data table
dt = Open("$Sample_Data/Consumer Preferences.jmp");
// Categorical Several
Categorical(
    X( :Age Group, :School Age Children ),
    Grouping Option(
        "Each Individually"
    ),
    Responses(
        :I am working on my career
    ),
    Responses(
        :
        My home needs some major improvements
    ),
    Responses(
        :
        I have vast interests outside of work
    ),
    Responses(
        :I come from a large family
    ),
    Crosstab Transposed( 1 ),
    Legend( 0 ),
    Test Response Homogeneity( 1 )
);

Example 3

Summary: Perform categorical analysis with crosstab transposed and test for response homogeneity

Code:

// Open data table
dt = Open("$Sample_Data/Consumer Preferences.jmp");
// Career by Age Group
Categorical(
    X( :Age Group ),
    Responses(
        :I am working on my career
    ),
    Crosstab Transposed( 1 ),
    Legend( 0 ),
    Test Response Homogeneity( 1 )
);

Example 4

Summary: Perform categorical analysis with crosstab transposed and test for response homogeneity

Code:

// Open data table
dt = Open("$Sample_Data/Consumer Preferences.jmp");
// Home Needs Improve by School Children
Categorical(
    X( :School Age Children ),
    Responses(
        :
        My home needs some major improvements
    ),
    Crosstab Transposed( 1 ),
    Legend( 0 ),
    Test Response Homogeneity( 1 )
);

Example 5

Summary: Perform categorical analysis with crosstab transposed and test for response homogeneity

Code:

// Open data table
dt = Open("$Sample_Data/Consumer Preferences.jmp");
// Vast Interests by School Children
Categorical(
    X( :School Age Children ),
    Responses(
        :
        I have vast interests outside of work
    ),
    Crosstab Transposed( 1 ),
    Legend( 0 ),
    Test Response Homogeneity( 1 )
);

Example 6

Summary: Perform categorical analysis with indicator group

Code:

// Open data table
dt = Open("$Sample_Data/Consumer Preferences.jmp");
// Brushing Indicator Group by Age
Categorical(
    X( :Age Group ),
    Indicator Group(
        :Brush After Waking Up,
        :Brush After Meal,
        :Brush Before Sleep,
        :Brush Another Time
    ),
    Share Of Responses( 0 ),
    Share Chart( 0 ),
    Frequency Chart( 1 ),
    Crosstab( 1 ),
    Legend( 0 ),
    Test Each Response( 1 )
);

Example 7

Summary: Perform categorical analysis with indicator group

Code:

// Open data table
dt = Open("$Sample_Data/Consumer Preferences.jmp");
// Flossing Indicator by Age
Categorical(
    X( :Age Group ),
    Indicator Group(
        :Floss After Waking Up,
        :Floss After Meal,
        :Floss Before Sleep,
        :Floss Another Time
    ),
    Share Of Responses( 0 ),
    Share Chart( 0 ),
    Frequency Chart( 1 ),
    Crosstab Transposed( 1 ),
    Legend( 0 ),
    Test Each Response( 1 )
);

Example 8

Summary: Perform categorical analysis with multiple delimited and test each response

Code:

// Open data table
dt = Open("$Sample_Data/Consumer Preferences.jmp");
// Brushing Delimited by Age
Categorical(
    X( :Age Group ),
    Multiple Delimited(
        :Brush Delimited
    ),
    Share Chart( 0 ),
    Frequency Chart( 1 ),
    Crosstab Transposed( 1 ),
    Legend( 0 ),
    Test Each Response( 1 )
);

Example 9

Summary: Perform categorical analysis with multiple delimited and test each response

Code:

// Open data table
dt = Open("$Sample_Data/Consumer Preferences.jmp");
// Flossing Delimited by Age
Categorical(
    X( :Age Group ),
    Multiple Delimited(
        :Floss Delimited
    ),
    Share Of Responses( 0 ),
    Share Chart( 0 ),
    Frequency Chart( 1 ),
    Crosstab Transposed( 1 ),
    Legend( 0 ),
    Test Each Response( 1 )
);

Example 10

Summary: Perform categorical analysis with free text

Code:

// Open data table
dt = Open("$Sample_Data/Consumer Preferences.jmp");
// Free Text Floss Reasons
Categorical(
    Free Text(
        :Reasons Not to Floss,
        <<Score Words by Column( :Floss ),
        <<Save Word Table
    ),
    Crosstab Transposed( 1 ),
    Legend( 0 )
);

Example 11

Summary: Create a categorical analysis comparing various responses across different age groups using the Categorical function.

Code:

// Open data table
dt = Open("$Sample_Data/Discovery US 2018 Survey.jmp");
// Categorical by Age
Categorical(
    X( :Age ),
    Responses( :Handedness ),
    Responses( :Analysis ),
    Responses( :BBQ ),
    Responses( :Pie ),
    Responses( :Discoveries ),
    Responses( :OS ),
    Responses( :Usage ),
    Responses( :Boy Band ),
    Responses( :DGA ),
    Responses( :Type ),
    Legend( 0 )
);

Example 12

Summary: Categorize selected variables and create indicator groups for further analysis.

Code:

// Open data table
dt = Open("$Sample_Data/Quality Control/Failures3Indicators.jmp");
// Categorical
Categorical(
    X( :clean, :date ),
    Indicator Group(
        :contamination, :corrosion,
        :doping, :metallization,
        :miscellaneous, :oxide defect,
        :silicon defect
    )
);

Example 13

Summary: Analyze a dataset containing failure frequencies using categorical analysis with sample size, date, and multiple response variables.

Code:

// Open data table
dt = Open("$Sample_Data/Quality Control/Failure3Freq.jmp");
// Categorical
Categorical(
    Sample Size( :SampleSize ),
    X( :clean, :date ),
    Response Frequencies(
        :contamination, :corrosion,
        :doping, :metallization,
        :miscellaneous, :oxide defect,
        :silicon defect
    )
);

Example 14

Summary: Perform Categorical Multivariate ID Analysis using the Freq, ID, X, Multiple Response by ID, and Sample Size functions.

Code:

// Open data table
dt = Open("$Sample_Data/Quality Control/Failure3ID.jmp");
// Cat MultID
Categorical(
    Freq( :N ),
    ID( :ID ),
    X( :clean ),
    Multiple Response by ID( :failure ),
    Sample Size( :SampleSize )
);

Example 15

Summary: Apply categorical multivariate ID analysis using the Categorical platform with frequency, ID, X, multiple response by ID, and sample size configurations.

Code:

// Open data table
dt = Open("$Sample_Data/Quality Control/Failure3ID.jmp");
// Cat MultID2
Categorical(
    Freq( :N ),
    ID( :ID ),
    X( :clean, :date ),
    Multiple Response by ID( :failure ),
    Sample Size( :SampleSize )
);

Example 16

Summary: Create a categorical analysis for variables and generate a frequency chart in the Categorical platform.

Code:

// Open data table
dt = Open("$Sample_Data/Quality Control/Failure3MultipleField.jmp");
// Categorical
Categorical(
    X( :clean, :date ),
    Multiple Response(
        :Failure1, :Failure2, :Failure3
    ),
    Frequency Chart( 0 )
);

Example 17

Summary: Run Categorical Delimited analysis using the Categorical function with specified variables from the Failures3Delimited data table.

Code:

// Open data table
dt = Open("$Sample_Data/Quality Control/Failures3Delimited.jmp");
// Categorical Delimited
Categorical(
    ID( :ID ),
    X( :clean, :date ),
    Multiple Delimited( :failureS )
);

Example 18

Summary: Create a categorical analysis with the 'Sex' and 'Passenger Class' variables, separate responses by 'Survived' and display results in a crosstab format.

Code:

// Open data table
dt = Open("$Sample_Data/Titanic Passengers.jmp");
// Categorical
Categorical(
    X( :Sex, :Passenger Class ),
    Separate Responses( :Survived ),
    Crosstab Format( 1 ),
    Legend( 0 )
);