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Chapter4a - STA2023 Chapter 4a(Displaying Quantitative Data...

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1 STA2023 - Chapter 4a (Displaying Quantitative Data) As mentioned in chapter 3, graphs can reveal important information that a numerical analysis may hide. As such, chapter 4 extends the concept of graphing data – this time for quantitative data. This chapter also begins the introduction of numerical analysis of data. Recall that a quantitative variable can be measured numerically, with units of measurement. Histograms and Stemplots (stem-and-leaf displays) are common graphical methods we will use for quantitative data. We will be skipping dotplots – they are briefly discussed on page 52 of the book (if interested). Histograms : see pages 49-50 for an example Used for quantitative data only (not categorical data) Both axes must be labeled (variable on x-axis, frequency or relative frequency on y-axis) Must use consistent scaling on each axis (this results in bars of equal width) No spaces/gaps between the bars (unlike bar charts) Usually, any observation on the line between two bars goes into the upper bar (see box on page 49) Can be made on a graphing calculator (change width of the bars by changing the Xscl) Activity 1 (page 85, #54) In 2006, Inc . magazine (www.inc.com) listed its choice “boomtowns” in the United States – larger cities that are growing rapidly. Here is the magazine’s top 20, along with their 1-year job growth percentages: Las Vegas, NV 7.50% Jacksonville, FL 2.60% Fort Lauderdale, FL 4.20% Charlotte, NC 3.30% Orlando, FL 4.50% Raleigh-Cary, NC 2.80% West Palm Beach, FL 3.40% Richmond, VA 2.90% San Bernadino, CA 1.90% Salt Lake City, UT 3.30% Phoenix, AZ 4.40% Putnam County, NY 2.30% Northern Virginia, VA 3.10% Santa Ana, CA 1.70% Washington, DC 3.20% Miami, FL 2.20% Tampa, FL 2.60% Sacramento, CA 1.50% Camden County, NJ 2.60% San Diego, CA 1.40% A. Use your graphing calculator to make a histogram of the given data.
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