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2: Graphical Descriptions of Data

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    In chapter 1, you were introduced to the concepts of population, which again is a collection of all the measurements from the individuals of interest. Remember, in most cases you can’t collect the entire population, so you have to take a sample. Thus, you collect data either through a sample or a census. Now you have a large number of data values. What can you do with them? No one likes to look at just a set of numbers. One thing is to organize the data into a table or graph. Ultimately though, you want to be able to use that graph to interpret the data, to describe the distribution of the data set, and to explore different characteristics of the data. The characteristics that will be discussed in this chapter and the next chapter are:

    1. Center: middle of the data set, also known as the average.
    2. Variation: how much the data varies.
    3. Distribution: shape of the data (symmetric, uniform, or skewed).
    4. Qualitative data: analysis of the data
    5. Outliers: data values that are far from the majority of the data.
    6. Time: changing characteristics of the data over time.

    This chapter will focus mostly on using the graphs to understand aspects of the data, and not as much on how to create the graphs. There is technology that will create most of the graphs, though it is important for you to understand the basics of how to create them.

    This page titled 2: Graphical Descriptions of Data is shared under a CC BY-SA 4.0 license and was authored, remixed, and/or curated by Kathryn Kozak via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.