Course
IND2249070
APPLIED STATISTICS
Industrial Engineering
- LECTURE
- 3
- LAB
- 0
- CREDITS
- 3
- ECTS
- 6
REQUIRES
REQUIRED BY
TAUGHT IN
AIM
This course aims to provide basic statistical techniques in order to collect, analyze and interpret data with emphasis on engineering applications.
CONTENT
This course contains; Introduction to Statistics and Data Analysis,Sampling Distributions,Sampling Distributions and Estimation,Confidence Intervals-Single Population I,Hypothesis Testing- Single Population I,Confidence Intervals- Two Populations I,Confidence Intervals- Two Populations II,Hypothesis Testing- Two Populations I,Hypothesis Testing- Two Populations II,Introduction to Correlation and Regression Analysis,Linear Regression Models,Linear Regression Models,Multiple Regression Models,Advanced Topics in Multiple Regression Models.
LEARNING OUTCOMES
- 1
Construct and interpret graphical and/or numerical summaries of data.
Taught by: Question - Answer Technique, Lecture Method · Assessed by: Traditional Written Exam
- 2
Distinguish between a population and a sample.
Taught by: Self Study Method, Question - Answer Technique, Lecture Method · Assessed by: Traditional Written Exam, Quiz
- 3
Construct confidence intervals for population characteristics
Taught by: Problem Solving Method, Self Study Method, Question - Answer Technique, Lecture Method · Assessed by: Traditional Written Exam, Homework, Quiz
- 4
Construct hypothesis tests for population characteristics.
Taught by: Problem Solving Method, Question - Answer Technique, Lecture Method · Assessed by: Traditional Written Exam, Homework, Quiz
- 5
Carry out correlation and regression analysis
Taught by: Problem Solving Method, Question - Answer Technique, Lecture Method · Assessed by: Traditional Written Exam, Homework, Quiz
- 6
Use statistical package SPSS to carry out the statistical procedures discussed during the semester.
Taught by: Demonstration Method, Lecture Method · Assessed by: Traditional Written Exam, Homework
WEEKLY PLAN
- WEEK 1
Introduction to Statistics and Data Analysis
Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 1
- WEEK 2
Sampling Distributions
Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 8
- WEEK 3
Sampling Distributions and Estimation
Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 8
- WEEK 4
Confidence Intervals-Single Population I
Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 9
- WEEK 5
Hypothesis Testing- Single Population I
Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 10
- WEEK 6
Confidence Intervals- Two Populations I
Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 9
- WEEK 7
Confidence Intervals- Two Populations II
Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 9
- WEEK 8
Hypothesis Testing- Two Populations I
Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 10
- WEEK 9
Hypothesis Testing- Two Populations II
Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 10
- WEEK 10
Introduction to Correlation and Regression Analysis
Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 11
- WEEK 11
Linear Regression Models
Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 11
- WEEK 12
Linear Regression Models
Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 11
- WEEK 13
Multiple Regression Models
Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 12
- WEEK 14
Advanced Topics in Multiple Regression Models
Preparation: Lecture Notes
ASSESSMENT
- Rate of Midterm Exam to Success30%
- Rate of Final Exam to Success70%
WORKLOAD
| ACTIVITY | COUNT | HOURS | TOTAL |
|---|---|---|---|
| Course Hours | 14 | 3 | 42 |
| Guided Problem Solving | 14 | 2 | 28 |
| Resolution of Homework Problems and Submission as a Report | 3 | 10 | 30 |
| Term Project | 1 | 8 | 8 |
| Presentation of Project / Seminar | 0 | 0 | 0 |
| Quiz | 3 | 10 | 30 |
| Midterm Exam | 1 | 20 | 20 |
| General Exam | 1 | 22 | 22 |
| Performance Task, Maintenance Plan | 0 | 0 | 0 |
READING
- Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson.
- Douglas C. Montgomery & George C. Runger. "Applied Statistics and Probability for Engineers", Wiley
TEACHING STAFF
- Assist.Prof. Rüçhan Melisa DENİZ ÖZGENCOORDINATOR
- Assist.Prof. Rüçhan Melisa DENİZ ÖZGEN