Help Guide: Crosstabulation (Association of Attributes) in OPSTAT

Introduction to Crosstabulation

Crosstabulation, also known as a contingency table, is a method used to analyze the relationship between two or more categorical variables. It allows you to observe the frequency distribution of the variables and helps in testing hypotheses about their association.

Where is Crosstabulation Used?

Crosstabulation is commonly used in fields such as social sciences, marketing, healthcare, and other disciplines where the relationship between different categorical variables is studied. For example:

• Determining the association between gender and preference for a particular product.
• Analyzing the relationship between education level and employment status.
• Investigating the link between treatment type and recovery rate in medical studies.

Null and Alternative Hypotheses

In crosstabulation, the following hypotheses are typically tested:

• Null Hypothesis (H₀): There is no association between the variables. In other words, the variables are independent.
• Alternative Hypothesis (H₁): There is an association between the variables. The variables are not independent.

To test the association, you can use statistical tests such as Chi-Square, which evaluates whether the observed frequency distribution differs from the expected distribution.

How to Enter Data and Character Names

In the OPSTAT Crosstabulation tool, you will be required to enter the data and character (variable) names. Here’s how to do it:

1. Enter or Paste Data: Use the large input area labeled “Please Enter or Paste Data.” You can input your data in a tab or space-delimited format. Ensure that the data follows a consistent structure.
2. Enter Character Names: Use the smaller input area labeled “Enter Character Names” to input the names of the variables (characters) in your dataset. Each name should correspond to a column of data.

How to Use the OPSTAT Crosstabulation Tool

Follow these steps to use the Crosstabulation tool in OPSTAT:

1. Navigate to the Crosstabulation tool page.
2. Input your data and character names in the respective text areas.
3. Click the “Submit” button to proceed to the next screen, where you’ll specify additional parameters such as the number of variables, observations per variable, and the variables you want to use for rows and columns in the contingency table.
4. Select the desired cell content options (Row Percent, Column Percent, etc.) and statistics (Chi-Square, Phi, etc.) to display in your results.
5. Click “Analyse” to view the results of the Crosstabulation, including the contingency table and relevant statistical outputs.

Example of Data Input

Here’s a simple example of how your data might look when entered:

1  0  1
1  1  0
0  1  1
0  0  0
    

And the corresponding character names:

Gender
Preference
Purchase
    

Interpreting the Results

After running the analysis, the tool will generate a contingency table showing the distribution of variables across the categories. If selected, you will also receive additional statistics such as Chi-Square, Phi, and Contingency Coefficient to help interpret the strength and significance of the association between the variables.