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Lecture Statistical techniques in business and economics - Chapter 2: Describing data: frequency distribution and graphic presentation

When you have completed this chapter, you will be able to: Organize raw data into frequency distribution; produce a histogram, a frequency polygon, and a cumulative frequency polygon from quantitative data; develop and interpret a stem-and-leaf display; present qualitative data using such graphical techniques such as a clustered bar chart, a stacked bar chart, and a pie chart; detect graphic deceptions and use a graph to present data with clarity, precision, and efficiency. | Describing Data requency Distributions f Graphic Presentations & Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 2 Chapter Goals Organize raw data into frequency distribution Produce a histogram, a frequency polygon, and a cumulative frequency polygon from quantitative data Develop and interpret a stem-and-leaf display When you have completed this chapter, you will be able to: and. Present qualitative data using such graphical techniques such as a clustered bar chart, a stacked bar chart, and a pie chart Detect graphic deceptions and use a graph to present data with clarity, precision, and efficiency Chapter Goals Frequency Distribution A Frequency Distribution is a grouping of data into non-overlapping classes (mutually exclusive) showing the number of observations in each category or class. The range of categories includes all values in the data set (collectively exhaustive classes). Frequency Distribution Frequency Distribution Definitions . | Describing Data requency Distributions f Graphic Presentations & Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 2 Chapter Goals Organize raw data into frequency distribution Produce a histogram, a frequency polygon, and a cumulative frequency polygon from quantitative data Develop and interpret a stem-and-leaf display When you have completed this chapter, you will be able to: and. Present qualitative data using such graphical techniques such as a clustered bar chart, a stacked bar chart, and a pie chart Detect graphic deceptions and use a graph to present data with clarity, precision, and efficiency Chapter Goals Frequency Distribution A Frequency Distribution is a grouping of data into non-overlapping classes (mutually exclusive) showing the number of observations in each category or class. The range of categories includes all values in the data set (collectively exhaustive classes). Frequency Distribution Frequency Distribution Definitions Class Midpoint or Class Mark: A point that divides a class into two equal parts, i.e. the average of the upper and lower class limits. 12.5 Class frequency: The number of observations in each class. Class interval: The class interval is obtained by subtracting the lower limit of a class from the lower limit of the next class, e.g. 5 17.5 22.5 27.5 32.5 EXAMPLE Dr. Tillman is Dean of the School of Business. He wishes to prepare a report showing the number of hours per week students spend studying. He selects a random sample of 30 students and determines the number of hours each student studied last week. 15.0, 23.7, 19.7, 15.4, 18.3, 23.0, 14.2, 20.8, 13.5, 20.7, 17.4, 18.6, 12.9, 20.3, 13.7, 21.4, 18.3, 29.8, 17.1, 18.9, 10.3, 26.1, 15.7, 14.0, 17.8, 33.8, 23.2, 12.9, 27.1, 16.6. Required: Organize the data into a frequency distribution. Q uestion Decide how many classes you wish to use. Frequency Distributions by hand Determine the class width. There are five steps that can be used to