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Lecture Notes MSE 601 Engineering Statistics Ahmad R. Sarfaraz Manufacturing Systems Engineering and Management California State University, Northridge Copyright © 2002. All Rights Reserved. Overview Of Chapter 1 • • • • • What is Statistics? Areas of statistics Why Study Statistics? Road Map of the Reasons for Learning Statistical Thinking What is Statistics? • Many meanings – Used as a synonym for numerical information • Grades on students exams, Diameter of a ball bearing, Amount of reactant in a chemical experiment – Used as a body of knowledge that enables one to do the following: • • • • Draw useful conclusions from numerical information Make decisions in a rational way Predict and control events Increase quality and productivity Areas of Statistics • Descriptive Statistics – Methods dealing with conclusion, tabulation, summarization, and presentation of data • Inferential Statistics – Methods that permit one to reach conclusions and make estimates about populations based upon information from a sample Why Study Statistics? • Engineers are constantly dealing with numerical information that needs to be analyzed • Among the reasons: – To present and describe numerical information – To draw conclusions about large populations from sample information – To improve processes and enhance quality – To design experiments – To obtain reliable forecasts Road Map of the Reasons for Learning Drawing conclusions about populations based on only sample information Presenting and describing information Random sampling and data description Chapter 6 Probability Chapter 2 Point estimation of parameters Chapter 7 Discrete random variables and probability distributions Chapter 3 Statistical Intervals for a single sample Chapter 8 Continuous random variables and probability distributions Chapter 4 Test of hypotheses for a single sample Chapter 9 Process improvements Nonparametric Statistics Chapter 15 Test of hypotheses for two samples Chapter 10 Design of Experiments Statistical quality control Chapter 16 Design and analysis of single-factor experiments Chapter 13 Obtaining of reliable forecasts Sample linear regression and correlation Chapter 11 Design of experiments with several factors Chapter 14 Statistical Thinking: Understanding and Managing Variability • No two things are exactly the same • Variability is inherent in all things • Ability to identify, quantify, reduce, and control the kinds of variability that affect quality • Variability is not inherently undesirable