Learn basic concepts of probability and statistical inference, focusing on an intuitive approach to understanding concepts and methodologies. Get an introduction to statistical and critical thinking, including descriptive statistics, probability, sampling distributions, interval estimation, hypothesis testing and regression.
Prerequisite(s)
IE3101 Introduction to Probability
Corequisite(s)
None
Special Requisite(s)
Attendance is mandatory; students who have attended less than 60% of classes will receive zero points from the term project regardless of their exam grades. Each student is expected to actively participate in classroom discussions and exercises.
Monday 14:00-14:45 in Office 2-A-10
Wednesday 10:00-10:45 in Office 2-A-10
Teaching Methods and Techniques
-Lecture, question-answer, discussion, problem solving
Principle Sources
- Douglas C. Montgomery and George C. Runger , Statistics and Probability for Engineers, 6th edition, Wiley
-Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers and Keying Ye, Probability and Statistics for Engineers and Scientists, 8th Edition, Pearson Prentice Hall.
Other Sources
-
Course Schedules
Week
Contents
Learning Methods
1. Week
Probability Basics and Random Variables
Lecture, question-answer, discussion, problem solving
2. Week
Introduction to Statistics, Sample and Population Mean, Variance; Data Visualization Methods: Stem and Leaf Diagrams, Quartiles
Lecture, question-answer, discussion, problem solving
3. Week
Data Visualization Methods: Histograms, Box-Plots, and Probability Plots
Lecture, question-answer, discussion, problem solving
4. Week
Sampling Distribution of Means and Central Limit Theorem, Point Estimation
Lecture, question-answer, discussion, problem solving
5. Week
Confidence Intervals on the Mean of a Normal Distribution (Known Variance), Confidence Intervals on the Mean of a Normal Distribution (Unknown Variance)
Lecture, question-answer, discussion, problem solving
6. Week
Confidence Intervals on the Variance of a Normal Distribution, Large Sample Confidence Intervals for a Population Proportion, Tolerance and Prediction Intervals
Lecture, question-answer, discussion, problem solving
7. Week
Hypotheses Testing for a Single Sample (Known Variance): Type 1 and Type 2 Errors, Power of a Test
Lecture, question-answer, discussion, problem solving
8. Week
Ramadan Festival (Holiday)
9. Week
Midterm Exam
10. Week
Hypotheses Testing for a Single Sample (Known and Unknown Variance): z-test, t-test
Lecture, question-answer, discussion, problem solving
11. Week
Worker’s Day (Holiday)
12. Week
Hypotheses Testing for a Single Sample: Chi-square Test, Goodness of Fit Test, and Contingency Tables
Lecture, question-answer, discussion, problem solving
13. Week
Hypotheses Testing for Two Samples: Inference for a Difference of Two Means
Lecture, question-answer, discussion, problem solving
14. Week
Hypotheses Testing for Two Samples: Paired t-test, Inferences on the Variances of Two Normal Populations
Lecture, question-answer, discussion, problem solving
15. Week
FINAL EXAM
16. Week
FINAL EXAM
17. Week
FINAL EXAM
Assessments
Evaluation tools
Quantity
Weight(%)
Midterm(s)
1
35
Quizzes
3
10
Project(s)
1
15
Final Exam
1
40
Program Outcomes
PO-1
Ability to apply theoretical and practical knowledge gained by Mathematics, Science and their engineering fields and ability to use their knowledge in solving complex engineering problems.
PO-2
Ability of determining, defining, formulating and solving complex engineering problems; for that purpose develop the ability of selecting and implementing suitable models and methods of analysis.
PO-3
Ability of designing a complex system, process, device or product under real world constraints and conditions serving certain needs; for this purpose ability of applying modern design techniques
PO-4
Ability of selecting and using the modern techniques and devices which are necessary for analyzing and solving complex problems in engineering implementations; ability of efficient usage of information technologies.
PO-5
Ability of designing experiments, conducting tests, collecting data and analyzing and interpreting the solutions to investigate of complex engineering problems or discipline-specific research topics.
PO-6
Ability of working efficiently in intra-disciplinary and multi-disciplinary teams; individual working ability and habits.
PO-7
Ability of verbal and written communication skills; and at least one foreign language skills, ability to write effective reports and understand written reports, ability to prepare design and production reports, ability to make impressive presentation, ability to give and receive clear and understandable instructions
PO-8
Awareness of importance of lifelong learning; ability to access data, to follow up the recent innovation in science and technology for continuous self-improvement.
PO-9
Conformity to ethical principles; knowledge about occupational and ethical responsibility, and standards used in engineering applications.
PO-10
Knowledge about work life implementations such as project management, risk management and change management; awareness about entrepreneurship and innovativeness; knowledge about sustainable development.
PO-11
Knowledge about effects of engineering applications on health, environment and security in global and social dimensions, and on the problems of the modern age in engineering; awareness about legal outcomes of engineering solutions.
Learning Outcomes
LO-1
Has knowledge about the use of statistics in industrial engineering.
LO-2
Has the ability to apply the knowledge gained in statistics to engineering problems.
LO-3
Selects appropriate information technology and uses it effectively in statistical applications.
LO-4
Has the ability to collect data, analyze and interpret the results in order to make inferences about the population based on the sample in Industrial Engineering subjects.
LO-5
Can receive and give clear instructions in studies to be carried out in order to apply statistical knowledge to engineering subjects.
