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Engineering Probability and
Statistics - SE-205 -Chap 1
By
S. O. Duffuaa
Course Objectives
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Introduce the students to basic
probability and statistics and
demonstrate its wide application in
the area of Systems Engineering.
Main Course Outcomes
Students should be able to perform:
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Summarize and present data using graphs,
diagrams and point summaries.
Define, compute probability using basic
probability laws and concepts.
Define and describe a random variable.
Describe known probability distributions in terms
pmf/pdf, distribution function, mean, variance,
and suggest few applications for each distribution.
Main Course Outcomes
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Calculate probabilities from probability
mass and density functions..
Perform point and interval estimation.
Use a statistical package such as
Minitab/Statistica to solve problems in
data analysis, probability distribution, and
estimation.
Work in teams and communicate
effectively through class presentations and
group meetings.
Text Book and References
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“Applied Statistics and Probability for
Engineers “ by D. C. Montgomery and
Runger, 2007.
“Probability and Statistics for Engineers
and Scientists” 5th by Walpole and Mayers.
Statistics by Murry Speigel
Course Policy
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Home-works and attendance
Quizzes
Exam1
Exam II
Final Exam
15%
15%
20%
20%
30%
SE- 205 Place in SE Curriculum

Central Course
 Prerequisite for 7 SE courses
• SE 303, SE 320, SE 323, SE 325,
SE 447, SE 480, SE 463 and may be
others. See SE Curriculum Tree
Engineering Problem Solving
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Develop clear and concise problem
description
Identify the important factors in the
problem.
Propose a model for the problem
Conduct appropriate experimentation
Refine the model
Engineering Problem Solving
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Validate the solution
Conclusion and recommendations
Statistics
• Science of data collection,
summarization, presentation and
analysis for decision making.
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How to collect data ?
How to summarize it ?
How to present it ?
How do you analyze it and make
conclusions and correct decisions ?
Role of Statistics
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Many aspects of Engineering deals with
data – Product and process design
Identify sources of variability
Essential for decision making
Data Collection
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Observational study
• Observe the system
• Historical data
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The objective is to build a system model
usually called empirical models
Data Collection
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Design of experiment
• Plays key role in engineering design
Statistics
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Divided into :
• Descriptive Statistics
• Inferential Statistics
Forms of Data Description
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Point summary
 Tabular format
 Graphical format
 Diagrams
Point Summary
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Central tendency measures
• Mean  xi/n
• Median --- Middle value
• Mode --- Most frequent value
Point Summary
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Variability measures
• Range = Max xi - Min xi
• Variance = V =  (xi – x )2/ n-1
• Standard deviation = S
S = Square root (V)
• Coefficient of variation = S/ x
Dot Diagram

A diagram that has on the x-axis the points
plotted : Given the following grades of a
class:
50, 23, 40, 90, 95, 10, 80, 50, 75, 55, 60,
40.
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0
50
100
Dot Diagram

A diagram that has on the x-axis the points
plotted : Given the following grades of a
class:
50, 23, 40, 90, 95, 10, 80, 50, 75, 55, 60,
40.
.
.
.
.
0
50
100
Time Frequency Plot
15
14
13
12
11
y 10
9
8
7
6
5
0
10
20
30
Observation number
40
50
Time Frequency Plot
15
14
13
12
11
y 10
9
8
7
6
5
0
10
20
30
Observation number
40
50
Control Charts
105
Concentration
Upper control limit = 100.5
95
x = 91.50
85
Lower control limit = 82.54
75
0
10
20
Observation number
30