tailieunhanh - Lecture Statistical techniques in business and economics (14/e): Chapter 4 - Lind, Marchal, Wathen

Chapter 4 - Describing data: Displaying and exploring data. When you have completed this chapter, you will be able to: Develop and interpret a dot plot; develop and interpret a stem-and-leaf display; compute and understand quartiles, deciles, and percentiles; construct and interpret box plots; compute and understand the coefficient of skewness; draw and interpret a scatter diagram; construct and interpret a contingency table. | Describing Data: Displaying and Exploring Data Chapter 4 GOALS Develop and interpret a dot plot. Develop and interpret a stem-and-leaf display. Compute and understand quartiles, deciles, and percentiles. Construct and interpret box plots. Compute and understand the coefficient of skewness. Draw and interpret a scatter diagram. Construct and interpret a contingency table. 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. EXAMPLE Reported below are the number of vehicles sold in the last 24 months at Smith Ford Mercury Jeep, Inc., in Kane, Pennsylvania, and Brophy Honda Volkswagen in Greenville, Ohio. Construct dot plots and report . | Describing Data: Displaying and Exploring Data Chapter 4 GOALS Develop and interpret a dot plot. Develop and interpret a stem-and-leaf display. Compute and understand quartiles, deciles, and percentiles. Construct and interpret box plots. Compute and understand the coefficient of skewness. Draw and interpret a scatter diagram. Construct and interpret a contingency table. 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. EXAMPLE Reported below are the number of vehicles sold in the last 24 months at Smith Ford Mercury Jeep, Inc., in Kane, Pennsylvania, and Brophy Honda Volkswagen in Greenville, Ohio. Construct dot plots and report summary statistics for the two small-town Auto USA lots. Stem-and-Leaf Stem-and-leaf display is a statistical technique to present a set of data. Each numerical value is divided into two parts. The leading digit(s) becomes the stem and the trailing digit the leaf. The stems are located along the vertical axis, and the leaf values are stacked against each other along the horizontal axis. Two disadvantages to organizing the data into a frequency distribution: The exact identity of each value is lost Difficult to tell how the values within each class are distributed. EXAMPLE Listed in Table 4–1 is the number of 30-second radio advertising spots purchased by each of the 45 members of the Greater Buffalo Automobile Dealers Association last year. Organize the data into a stem-and-leaf display. Around what values do the number of advertising spots tend to cluster? What is the fewest number of spots purchased by a dealer? The largest number purchased? The standard deviation is the most