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Class boundaries should be reasonable numbers.Classes should have the same width (except for possible open-ended classes at the extreme low or extreme high ends).Classes should not have any gaps between them.The word “reasonable” in the last two points is very subjective. Some good practices for constructing tables for continuous variables are listed below. Counts of the number of data values within each class can now be made, resulting in a table of either a frequency distribution (raw counts) or of a relative frequency distribution (percentage). Once classes are established for a continuous variable, each data value will belong to one (and only one) class. Finally, if a class does not have a lower or upper class limit (e.g., “shorter than 4 feet” or “60 and older”), the class is said to be open ended. The class width is the difference between the upper class limit and the lower class limit. Each class has a lower class limit, which is the smallest value within the class, and an upper class limit, which is the largest value within the class. To get around this, categories are created using classes, or intervals (ranges) of numbers. In terms of summarizing techniques, the main difference between discrete data and continuous data is that continuous data cannot directly be put into frequency tables since they do not have any obvious categories (you cannot create a table or histogram with an infinite number of categories). If desired, put the leaves in numerical order to create an ordered stem-and-leaf plot.Įxample 1.3: Creating a Stem-and-Leaf PlotĬreate a stem-and-leaf plot of the following ACT scores from a group of college freshmen.Ĭontinuous data has an infinite number of possibilities (like weights, heights, and times).Create a key to guide interpretation of the stem‑and-leaf plot.Be sure to line up the leaves in straight columns so that the table is visually accurate. There should be as many leaves as there are data values. Each leaf will be listed as many times as it occurs in the original data set. Each stem is normally listed only once however, the stems are sometimes listed two or more times if splitting the leaves would make the data set’s features clearer. List each stem that occurs in the data set in numerical order.Create two columns, one on the left for stems and one on the right for leaves.A legend, sometimes called a key, should be included so that the reader can interpret the information. The leaves are usually the last digit in each data value and the stems are the remaining digits. A stem-and-leaf plot retains the original data. In other words, rectangles touch each other in a histogram.Ī stem-and-leaf plot is a graph of quantitative data that is similar to a histogram in the way that it visually displays the distribution. The main visual difference between a bar graph (qualitative data) and a histogram (quantitative data) is that there should be no horizontal spacing between numerical values along the horizontal axis. The discrete values taken by the data are labeled in ascending order across the horizontal axis, and a rectangle is drawn vertically so that the height of each rectangle corresponds to each discrete variable’s frequency or relative frequency. A bar graph for any type of quantitative data is called a histogram. Histogramsĭiscrete quantitative data can be presented in bar graphs in the same ways as qualitative data. The only difference is that instead of using category names, we use the discrete values taken by the data. Tablesĭiscrete quantitative data can be presented in tables in several of the same ways as qualitative data: by values listed in a table, by a frequency table, or by a relative frequency table. The methods for summarizing discrete data are similar to methods used for summarizing qualitative data, since discrete data can be put into separate categories. These plots are rarely used except as preliminary (quick-and-dirty) techniques for understanding your data. Two other summary methods for quantitative data are stem-and-leaf plots and dot-plots.
#Steps to making a histogram first make a table how to#
You will learn how to create tables and histograms of each type of data. There are more ways to summarize quantitative data than qualitative data because numerical data comes in two forms: discrete or continuous (as mentioned earlier).
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