8: Describing Data
- Page ID
- 113182
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Once we have collected data from surveys or experiments, we need to summarize and present the data in a way that will be meaningful to the reader. We will begin with graphical presentations of data then explore numerical summaries of data.
- 8.1: Presenting Categorical Data Graphically
- Categorical, or qualitative, data are pieces of information that allow us to classify the objects under investigation into various categories.
- 8.2: Presenting Quantitative Data Graphically
- Quantitative data can be summarized by frequency tables, and are commonly displayed as a histogram, frequency polygon or stem plot.
- 8.3: Measures of Central Tendency
- It is often desirable to use a few numbers to summarize a distribution. One important aspect of a distribution is where its center is located. Numbers that describe a distribution's center are called measures of central tendency.
- 8.4: Measures of Variation and Location
- In addition to the mean and median, which are measures of the "typical" or "middle" value, we also need a measure of how "spread out" or varied each data set is. There are several ways to measure this "spread" of the data.
- 8.5: Box Plots
- In addition to the mean and median, which are measures of the "typical" or "middle" value, we also need a measure of how "spread out" or varied each data set is. There are several ways to measure this "spread" of the data.
- 8.6: Correlation and Causation, Scatter Plots
- There are many studies that exist that show that two variables are related to one another. The strength of a relationship between two variables is called correlation. Variables that are strongly related to each other have strong correlation. However, if two variables are correlated it does not mean that one variable caused the other variable to occur.
- 8.7: Graphics in the Media
- There are many other types of graphs you will encounter in the media.