Analysing a single nominal variable
When you have a single nominal variable (e.g. marital status) you might be interested in how many respondents selected each of the options (e.g. how many are married, how many widowed, etc.). Then to visualise these results and last but not least to determine if any of the categories is chosen more often than the others (also in the population). The analysis breaks down into the following parts (for each part in this analysis a separate page was created):
Part 1: Descriptive analysis
Use descriptive statistics to get an impression of the data, using:
1) A frequency table with absolute- and relative frequencies
2) A visualisation of the data with a bar-chart
3) Some statistical measures for central tendency (the mode) and dispersion (variation ratio)
Part 2: Inferential statistics
After the first impression determine what can be said about the population based on your sample data by:
1) Determine if overall the percentages could be equal in the population (a Pearson Chi-square goodness-of-fit test)
2) if they are not, then determine which categories differ significantly (a post-hoc pairwise binomial test)
3) determine the effect sizes (Cramer's V and Relative Risks)
Part 3: Reporting
As the last step, you will need to write up all the results.
Let's begin with getting an impression of the results in the first part.
Single nominal variable