Download Lecture Notes MSE 601 Engineering Statistics Ahmad R. Sarfaraz

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
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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:
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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