WEEK 2 Describing categorical data, Frequency distribution of categorical data, Best practices for graphing categorical data, Mode and median for categorical variable

Data from categorical variable are described in both in graphical and tabular form.  Data for categorical variable organized into one of several groups (categories) and can  only be counted. Bar graphs (Pareto charts), pie charts and line graphs are used .  Categorical variables represent types of data which may be divided into groups. Examples of categorical variables are race, sex, age group, and educational level. While the latter two variables may also be considered in a numerical manner by using exact values for age and highest grade completed, it is often more informative to categorize such variables into a relatively small number of groups.

Frequency distributions are mostly used for summarizing categorical variables. That's because metric variables tend to have many distinct values. These result in huge tables and charts that don't give insight into your data. In this case, histograms are the way to go as they visualize frequencies for intervals of values rather than each distinct value.  Anyway. Let's look at some examples of frequency distributions. 

1. Frequency Distribution - Table

2. Relative Frequencies

Frequency distribution may contain relative frequencies: frequencies relative to (divided by) the total number of values. Relative frequencies are often shown as percentages or proportions.

3. Frequency Distributions - Cumulative Frequencies

A cumulative frequency is the number of times that a value and all values that precede it occur. That is, the frequencies accumulate over values -hence “cumulative”.  The same reasoning goes for cumulative relative frequencies

4. Frequency Distributions - Bar Charts

5. Frequency Distributions - Pie Charts