APPLIED STATISTICS for ENGINEERS

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,Hypothesis Testing- Single Population,Confidence Intervals- Two Populations I,Hypothesis Testing- Two Populations I,Hypothesis Testing- Two Populations II,Introduction to Regression and Correlation Analysis,Linear Regression Models I,Linear Regression Models II,Multiple Regression Models I,Multiple Regression Models II.

1. 1

   Implements the procedures learned throughout the semester with SPSS software.

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

2. 2

   Applies correlation and linear regression analyzes and interprets the results.

   Taught by: Problem Solving Method, Question - Answer Technique, Lecture Method · Assessed by: Traditional Written Exam, Homework, Quiz

3. 3

   Creates and interprets hypothesis tests for population characteristics.

   Taught by: Problem Solving Method, Lecture Method · Assessed by: Traditional Written Exam, Homework, Quiz

4. 4

   Creates and interprets confidence intervals for population characteristics.

   Taught by: Problem Solving Method, Question - Answer Technique, Lecture Method · Assessed by: Traditional Written Exam, Homework, Quiz

5. 5

   Makes the distinction between population and sample.

   Taught by: Lecture Method · Assessed by: Traditional Written Exam, Homework

6. 6

   Summarizes and interprets data using graphical and/or numerical methods.

   Taught by: Lecture Method · Assessed by: Traditional Written Exam

WEEKLY PLAN

1. WEEK 1

   Introduction to Statistics and Data Analysis

   Preparation: Lecture Notes

2. WEEK 2

   Sampling Distributions

   Preparation: Lecture Notes

3. WEEK 3

   Sampling Distributions and Estimation

   Preparation: Lecture Notes

4. WEEK 4

   Confidence Intervals- Single Population

   Preparation: Lecture Notes

5. WEEK 5

   Hypothesis Testing- Single Population

   Preparation: Lecture Notes

6. WEEK 6

   Confidence Intervals- Two Populations I

   Preparation: Lecture Notes

7. WEEK 8

   Hypothesis Testing- Two Populations I

   Preparation: Lecture Notes

8. WEEK 9

   Hypothesis Testing- Two Populations II

   Preparation: Lecture Notes

9. WEEK 10

   Introduction to Regression and Correlation Analysis

   Preparation: Lecture Notes

10. WEEK 11

    Linear Regression Models I

    Preparation: Lecture Notes

11. WEEK 12

    Linear Regression Models II

    Preparation: Lecture Notes

12. WEEK 13

    Multiple Regression Models I

    Preparation: Lecture Notes

13. WEEK 14

    Multiple Regression Models II

    Preparation: Lecture Notes

ASSESSMENT

• Rate of Midterm Exam to Success50%
• Rate of Final Exam to Success50%

WORKLOAD

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

• Assoc.Prof. Melis Almula KARADAYICOORDINATOR
• Assoc.Prof. Melis Almula KARADAYI