TAILIEUCHUNG - Lecture Basic statistics for business and economics - Chapter 4: Describing data: Displaying and exploring data
When you have completed this chapter, you will be able to: Construct and interpret a dot plot, identify and compute measures of position, construct and analyze a box plot, compute and describe the coefficient of skewness, create and interpret a scatter diagram, develop and explain a contingency table. | Describing Data: Displaying and Exploring Data Chapter 04 McGraw-Hill/Irwin Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved. LO 4-1 Construct and interpret a dot plot. LO 4-2 Identify and compute measures of position. LO 4-3 Construct and analyze a box plot. LO 4-4 Compute and describe the coefficient of skewness. LO 4-5 Create and interpret a scatter diagram. LO 4-6 Develop and explain a contingency table. LEARNING OBJECTIVES 4- Dot Plots A dot plot groups the data as little as possible and the identity of an individual observation is not lost. To develop a dot plot, each observation is simply displayed as a dot along a horizontal number line indicating the possible values of the data. If there are identical observations or the observations are too close to be shown individually, the dots are “piled” on top of each other. LO 4-1 Construct and interpret a dot plot. The Service Departments at Tionesta Ford Lincoln Mercury and Sheffield Motors, Inc., two of the four Applewood Auto Group Dealerships, were both open 24 days last month. Listed below is the number of vehicles serviced during the 24 working days at the two dealerships. Construct dot plots and report summary statistics to compare the two dealerships. 4- Quartiles, Deciles and Percentiles The standard deviation is the most widely used measure of dispersion. Alternative ways of describing spread of data include determining the location of values that divide a set of observations into equal parts. These measures include quartiles, deciles, and percentiles. To formalize the computational procedure, let Lp refer to the location of a desired percentile. So if we wanted to find the 33rd percentile, we would use L33, and if we wanted the median, the 50th percentile, then L50. The number of observations is n, so if we want to locate the median, its position is at (n + 1)/2, or we could write this as (n + 1)(P/100), where P is the desired percentile LO 4-2 Identify and .
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