📊 Topic Summary
Categorical data represents characteristics or qualities. Unlike numerical data, it can't be measured but can be divided into groups. Frequency tables organize this data by showing how often each category appears. They are essential for understanding patterns and distributions in categorical datasets.
Frequency tables provide a clear summary of categorical data, making it easier to identify the most common categories and understand the overall distribution. This is super useful for everything from market research to social sciences!
🔤 Part A: Vocabulary
Match the terms with their definitions:
| Term |
Definition |
| 1. Categorical Data |
A. The number of times a value occurs. |
| 2. Frequency |
B. Data that can be sorted into groups or categories. |
| 3. Frequency Table |
C. A table that displays the frequency of each category. |
| 4. Relative Frequency |
D. The proportion of times a value occurs. |
| 5. Percentage Frequency |
E. Relative frequency expressed as a percentage. |
✍️ Part B: Fill in the Blanks
Complete the following paragraph using the words: categorical, frequency, table, data, relative.
A __________ __________ is used to organize __________ data. This type of __________ shows the __________ of each category. We can also calculate __________ frequency to see the proportion of each category.
🤔 Part C: Critical Thinking
Why are frequency tables useful for analyzing categorical data? Give an example of a situation where using a frequency table would be helpful.