Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
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