1. Engineering Probability and Statistics - SE-205 -Chap 1By
S. O. Duffuaa

2. Course Objectives
To introduce students to basic concepts in probability and statistics to enable them to apply laws of probability, perform data analysis, estimation, make inference about populations and relate these concepts to practice

3. Main Course Outcomes
Students should be able to perform:
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.
Calculate probabilities from probability mass and density functions.

4. Main Course Outcomes
Describe known probability distributions in terms pmf/pdf, distribution function, mean, variance, and suggest few applications for each distribution.
Perform point and interval estimation.
Use a statistical package such as Minitab and Excel to solve problems in data analysis, probability distribution, and estimation.

5. Text Book and References
“Applied Statistics and Probability for Engineers “ by D. C. Montgomery and Runger, 5th Edition, 2011.
“Statistical Procedures for Engineering, Management and Science”, by Leland Bland, McGraw-Hill, 1980.
“Probability and Statistics for Engineers and Scientists” 5th by Walpole and Mayers, 2008
Statistics by Murry Speigel

6. Course Policy Home-works and attendance 10% Quizzes 15% Exam1 20%
Exam II %
Final Exam %

7. SE- 205 Place in SE Curriculum Rational
Central Course
Prerequisite for 7 SE courses
I SE 303, SE 320, ISE 323, ISE 325, ISE 405, ISE 447, ISE 480, I SE 463 and may be others. See SE Curriculum Tree

8. Program Outcomes
apply knowledge of mathematics, science, and engineering;
design and conduct experiments, as well as analyze and interpret data;
design and improve integrated systems of people, materials, information, facilities, and technology;
function as a member of a multi-disciplinary team;
identify, formulate, and solve industrial and Systems engineering problems;

9. Program Outcomes
understand and respect professional and ethical responsibility;
communicate effectively both orally and in writing;
understand the impact of engineering solutions in a global and societal context;
recognize the need for life-long learning, and an ability to engage in it;

10. Program Outcomes have a knowledge of contemporary issues;
use up to dated techniques, skills and tools of Industrial and Systems Engineering throughout their professional careers

11. Engineering Problem Solving
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

12. Engineering Problem Solving
Manipulate the model to help in developing a solution.
Re-visit the experimentation to confirm results.
Validate the solution
Conclusion and recommendations

13. Statistics
Science of data collection, summarization, presentation and analysis for decision making.
How to collect data ?
How to summarize it ?
How to present it ?
How do you analyze it and make conclusions and correct decisions ?

14. Role of Statistics
Many aspects of Engineering deals with data – Product and process design
Identify sources of variability
Essential for decision making

15. 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. . . . . 50
100

16. 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. . . . . 50
100

17. Data Collection Three basic methods: Observational study
A retrospective study using historical data..
An observational study collect data by observing the system.
A designed experiment.
The objective is to build a system model usually called empirical models

18. Data Collection Design of experiment
Plays key role in engineering design

19. Statistics Divided into : Descriptive Statistics
Inferential Statistics

20. Forms of Data Description
Point summary
Tabular format
Graphical format
Diagrams

21. Point Summary Mean  xi/n Median --- Middle value
Central tendency measures
Mean  xi/n
Median --- Middle value
Mode --- Most frequent value

22. Point Summary Range = Max xi - Min xi Variance = V =  (xi – x )2/ n-1
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

23. 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. . . . . 50
100

24. 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. . . . . 50
100

25. Time Frequency Plot

26. Time Frequency Plot

27. Control Charts Upper control limit = 100.5 x = 91.50
Lower control limit = 82.54