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Course

IND2249070

APPLIED STATISTICS

Industrial Engineering

LECTURE
3
LAB
0
CREDITS
3
ECTS
6
LANGUAGEEnglishLEVELFirst Cycle (Bachelor's Degree)TYPERequired

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. 1

    Construct and interpret graphical and/or numerical summaries of data.

    Taught by: Question - Answer Technique, Lecture Method · Assessed by: Traditional Written Exam

  2. 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. 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. 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. 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. 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

  1. WEEK 1

    Introduction to Statistics and Data Analysis

    Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 1

  2. WEEK 2

    Sampling Distributions

    Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 8

  3. WEEK 3

    Sampling Distributions and Estimation

    Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 8

  4. WEEK 4

    Confidence Intervals-Single Population I

    Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 9

  5. WEEK 5

    Hypothesis Testing- Single Population I

    Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 10

  6. WEEK 6

    Confidence Intervals- Two Populations I

    Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 9

  7. WEEK 7

    Confidence Intervals- Two Populations II

    Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 9

  8. WEEK 8

    Hypothesis Testing- Two Populations I

    Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 10

  9. WEEK 9

    Hypothesis Testing- Two Populations II

    Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 10

  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

  11. WEEK 11

    Linear Regression Models

    Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 11

  12. WEEK 12

    Linear Regression Models

    Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 11

  13. WEEK 13

    Multiple Regression Models

    Preparation: Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 12

  14. 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

ACTIVITYCOUNTHOURSTOTAL
Course Hours14342
Guided Problem Solving14228
Resolution of Homework Problems and Submission as a Report31030
Term Project188
Presentation of Project / Seminar000
Quiz31030
Midterm Exam12020
General Exam12222
Performance Task, Maintenance Plan000

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