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More Chapter 3!

More Chapter 3!. (or Chapter 4). Brave New Data. We are no longer limited to charts which only work for categorical data. We have three more charts at our disposal.

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More Chapter 3!

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  1. More Chapter 3! (or Chapter 4)

  2. Brave New Data • We are no longer limited to charts which only work for categorical data. • We have three more charts at our disposal. • Even though I do not think the book stresses this enough, frequency tables and relative frequency tables are still useful for quantitative data. • Bar charts and pie charts, however, are not.

  3. Just Kidding On The Bar Charts • We do not use bar charts (or column charts) for quantitative data. • We use histograms. • These are, as you can hopefully see, charts with bars. • Doesn’t that make them bar charts?

  4. It Totally Should • Distinguishing between histograms and bar charts borders on obnoxiousness. • However, it is important to note that bar charts have gaps and histograms do not, and so we call them something different. • The primary purpose in the distinction is help reinforce that categorical data and quantitative data are different.

  5. What Makes Histograms Special • Bar charts can show data in whatever order they like, but histograms need to go in order. • Since they are used with quantitative data, the order is built in. • If there is an interval with no data, you are still expected to have it in your graph as an empty space. • A gap on a histogram means there was a gap in the data.

  6. Categorical vs. Quantitative • Sometimes the data can be made into either. • For example, scores and letter grades can both be found for the quiz.

  7. Histograms FTW! • In later chapters, histograms will be the preferred plot for categorical data in general. • Dotplots are a fun way to amuse yourself…if you are into making charts and graphs. • Stem-and-leaf plots are useful, but can take forever and also require intense attention to detail. • They are very convenient for displaying two distributions side by side. • While not mentioned much in this chapter, there are also lineplots, which are like histograms, except instead of bars, there is a line connecting the frequencies.

  8. Stem-and-leaf Diagrams • Also known as stemplots. • The stem contains the beginning of each data point (such as the tens place or hundreds place). • Each data point is called a leaf. • Each leaf needs to be the same number of characters. • If you have double-digit leaves, it is wise to leave a space after each one.

  9. Stem-and-leaf Diagrams • The stem can be broken down into partial categories, such as high and low. • The stem can be surrounded on both sides with leaves, representing two distributions side by side. • The leaves need to all take up the same space. • On a computer, the Courier font ensures that all text takes up the same space left to right.

  10. Stem-and-leaf Diagrams • The leaves should be in numerical order within each stem. • This means sorting the data first. • No stem should be left out, which means that if you do not have any leaves for a given stem, you still need it, but it just gets left empty. • Probably best done by hand, and for relatively small data sets (like 30 subjects or less).

  11. Back to Histograms • Histograms should be evenly scaled. • This means even class widths. • The book would say even bin sizes. • This also can be expressed as even intervals. • Histograms should include every interval between the start and stop of the data. • Even if they are empty. • Especially if they are empty.

  12. Assignments • Read Chapter 4. • Make time to see or e-mail me with quiz questions. • Begin studying for Chapter 4 Quiz on Thursday.

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