Transcript Chapter 19
Data Analysis and Data Presentation Chapter 19 Achieving Quality Through Continual Improvement Claude W. Burrill / Johannes Ledolter Published by John Wiley & Sons, Inc., 1999 Prepared by Dr. Tomi Wahlström, University of Southern Colorado Chapter 19 1 Introduction • Data need to be summarized and displayed so that its meaning can be shared with all parties involved • 80-20 rule: 80% of what you are interested in is concentrated in 20% of the observations • Basic statistical principles must be understood by everyone in the organization Chapter 19 2 Organizing Data-The Pareto Diagram • The relative frequencies are displayed in the form of a bar chart, with the heights of the bars representing the frequencies of the various groups • It is easy to organize data by the type of defect: • Collect data for the problem • Classify the data into about a half-dozen categories, one of which might be “other” • List each class and the number of its members in order starting with the most frequent class Chapter 19 3 Data Presentation • Since many people don’t feel comfortable with numbers, graphical tools must be employed to communicate data • Due to desktop computers, drawing graphs has become effective and efficient improving the way data is presented Chapter 19 4 Graphical Displays of a Data Set • Time-sequence display – Measurements plotted against time • Dot diagram – Each measurement is represented on a horizontal line by a dot that indicates is magnitude • Histogram – Range of observations divided into nonoverlapping intervals Chapter 19 5 Summary Statistics of a Data Set: Descriptive Statistics • Measures of central tendency – Mean: sum of the data elements divided by the number of data elements – Median: middle-most data element after the data have been arranged according to size – Mode: data element appearing with the highest frequency Chapter 19 6 Descriptive Statistics • Measures of Variability – Variance: based on the squared differences between the data elements and the average – Standard deviation: square root of the variance – Range: the difference between the largest and the smallest data element • Descriptive statistics help us track performance over time Chapter 19 7 Scatter Diagrams and Correlation Coefficient • Scatter diagrams help us in a graphical form to see how two or more variables are correlated • Correlation coefficient is a numerical value to represent this correlation – It measures linear association only – Separate from cause-and-effect Chapter 19 8 The Normal Distribution • An important model to describe variability – Most commonly encountered continuous random variable is the normal random variable whose values are distributed according to a bell-shaped curve (normal curve) – 68% of population lies within 1 SD of the mean • 95% of population lies within 2 SD of the mean • 99.7% of population lies within 3 SD of the mean • Central limit theorem Chapter 19 9 Random Sampling • The process of selecting members from the population is called sampling from a population • Selected elements represent a sample • Number of elements is referred as sample size (n) • Random sample: each possible sample has the same change to be selected Chapter 19 10 Things to Watch When Displaying Information • Cutting off the bottoms of a bar chart – Bottom trick • Using a wrong display of area – Dimensional effect • Use of symbols can be misleading Chapter 19 11 Questions? Chapter 19 12 Copyright© 1999 John Wiley & Sons Inc. All rights reserved. Reproduction or translation of this work beyond that permitted in section 117 of the United States Copyright Act without the express written permission of the copyright owner is unlawful. Request for further information should be addressed to the permission department, John Wiley & Sons, Inc. The purchaser may make back-up copies for his/her own use only and not for distribution or resale. The Publisher assumes no responsibility for errors, omissions, or damages, caused by the use of these programs or from the use of the information contained herein. Chapter 19 13