This page would contain resource information like a glossary of terms from the section, key equations, and a reminder of concepts that were covered.
Make this more relevant to what students want — help them to build their processes, study guides, mnemonics, and memory dump material.
Essential Concepts
- Categorical variables have distinguishing features placing individuals into one of several groups such as eye color, zip code, education level, and gender. The data from these variables can be displayed in multiple ways.
- Frequency tables, bar graphs, and pie charts are created to display the distribution of categorical variables.
- Completing frequency tables can be done by hand, but technology is needed to display frequency tables for larger datasets.
- Bar graphs and pie charts provide visual summaries of data that help us quickly identify how the individual category frequencies relate to one another and to the total count.
- The data distributions that result in using technology to create graphical displays (frequency tables, bar graphs, and pie charts) are used to answer questions about categorical variables.
Key Equations
- Converting a fraction to a proportion
[latex]\dfrac{\text{frequency (count)}}{\text{total frequency}}[/latex]
- Converting a proportion to a percentage
[latex]\text{proportion (decimal form)} \times100[/latex], then append a percent symbol, %.
- Converting a percentage into a number given a total
[latex]\text{percentage (decimal form)} \times\text{total number given}[/latex]
Glossary
- frequency
- the number of times an event or a value occurs. It is commonly referred to as the count.
- frequency table
- a table that lists the number of observations (the frequency or count) of each unique value of a categorical variable.
- relative frequency
- the proportion of observations that are in a particular category and can be expressed as a decimal or a percentage.
- bar graph
- a graph in which the categories are represented by bars that are separated from each other.
- pie chart
- a chart in which categories are represented by wedges in a circle and are proportional in size to the percentage of individuals/items in each category.
- categorical variable
- a variable that places an individual into one of several groups.
- quantitative variable
- a variable that takes numerical values that can be used in arithmetic.
- dataset
- a collection of data.
Put formal DCMP I Can statements to prepare for the self-check.
These I Can Statements are new (the first one is the “you will understand” rephrased as an I Can):
- I can display categorical data in multiple ways.
- I can create frequency tables to display the distribution of categorial variables.
- I can create bar graphs to display the distribution of categorial variables.
- I can create pie charts to display the distribution of categorial variables.
- I can use data distributions displayed in tables and graphs to answer research questions.
