Explain what nominal distribution means.

Nominal distribution, also known as categorical distribution, is a statistical distribution used for variables that have categories or levels. These categories or levels are mutually exclusive, meaning that an observation can only belong to one category or level.

Here are the steps to understand nominal distribution:

1. Identify the Variable: The first step in understanding nominal distribution is to identify the variable that is being measured. This variable should be categorical in nature. For example, the variable could be "color of a car" with categories like "red", "blue", "green", etc.

2. Understand the Categories: Each category or level of the variable is distinct and has no order or hierarchy. This means that no category is inherently better or worse than another. For example, in the "color of a car" example, no color is considered better or worse than another.

3. Collect Data: Data is collected for each category. This could be the number of observations that fall into each category. For example, you might collect data on the number of cars of each color.

4. Analyze the Distribution: The distribution of the data across the categories is then analyzed. This can show if one category has more observations than another. For example, you might find that there are more blue cars than red or green cars.

5. Interpret the Results: The results of the analysis can then be interpreted. This might involve making conclusions about the population based on the data. For example, you might conclude that blue is the most popular car color.

In summary, a nominal distribution is a type of statistical distribution used for categorical variables. It involves identifying the variable, understanding the categories, collecting data, analyzing the distribution, and interpreting the results.