Course Detail
Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| APPLIED STATISTICS | - | Spring Semester | 3+0 | 3 | 6 |
| Course Program |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | English |
| Course Level | First Cycle (Bachelor's Degree) |
| Course Type | Elective |
| Course Coordinator | Assist.Prof. Rüçhan Melisa DENİZ ÖZGEN |
| Name of Lecturer(s) | |
| Assistant(s) | Res. Asst. Ahmed ŞENGİL ([email protected]) |
| Aim | This course aims to provide basic statistical techniques in order to collect, analyze and interpret data with emphasis on engineering applications. |
| Course 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. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| Construct and interpret graphical and/or numerical summaries of data. | 16, 9 | A |
| Distinguish between a population and a sample. | 14, 16, 9 | A, G |
| Construct confidence intervals for population characteristics | 12, 14, 16, 9 | A, E, G |
| Construct hypothesis tests for population characteristics. | 12, 16, 9 | A, E, G |
| Carry out correlation and regression analysis | 12, 16, 9 | A, E, G |
| Use statistical package SPSS to carry out the statistical procedures discussed during the semester. | 11, 9 | A, E |
| Teaching Methods: | 11: Demonstration Method, 12: Problem Solving Method, 14: Self Study Method, 16: Question - Answer Technique, 9: Lecture Method |
| Assessment Methods: | A: Traditional Written Exam, E: Homework, G: Quiz |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Introduction to Statistics and Data Analysis | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 1 |
| 2 | Sampling Distributions | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 8 |
| 3 | Sampling Distributions and Estimation | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 8 |
| 4 | Confidence Intervals-Single Population I | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 9 |
| 5 | Hypothesis Testing- Single Population I | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 10 |
| 6 | Confidence Intervals- Two Populations I | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 9 |
| 7 | Confidence Intervals- Two Populations II | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 9 |
| 8 | Hypothesis Testing- Two Populations I | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 10 |
| 9 | Hypothesis Testing- Two Populations II | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 10 |
| 10 | Introduction to Correlation and Regression Analysis | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 11 |
| 11 | Linear Regression Models | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 11 |
| 12 | Linear Regression Models | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 11 |
| 13 | Multiple Regression Models | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 12 |
| 14 | Advanced Topics in Multiple Regression Models | Lecture Notes |
| Resources |
| 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 |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | An ability to apply knowledge of mathematics, science, and engineering | X | |||||
| 2 | An ability to identify, formulate, and solve engineering problems | X | |||||
| 3 | An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability | ||||||
| 4 | An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice | X | |||||
| 5 | An ability to design and conduct experiments, as well as to analyze and interpret data | X | |||||
| 6 | An ability to function on multidisciplinary teams | X | |||||
| 7 | An ability to communicate effectively | ||||||
| 8 | A recognition of the need for, and an ability to engage in life-long learning | ||||||
| 9 | An understanding of professional and ethical responsibility | ||||||
| 10 | A knowledge of contemporary issues | ||||||
| 11 | The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context | ||||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 30 | |
| Rate of Final Exam to Success | 70 | |
| Total | 100 | |
| ECTS / Workload Table | ||||||
| Activities | Number of | Duration(Hour) | Total Workload(Hour) | |||
| 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 | |||
| Total Workload(Hour) | 180 | |||||
| Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(180/30) | 6 | |||||
| ECTS of the course: 30 hours of work is counted as 1 ECTS credit. | ||||||
Detail Informations of the Course
Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| APPLIED STATISTICS | - | Spring Semester | 3+0 | 3 | 6 |
| Course Program |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | English |
| Course Level | First Cycle (Bachelor's Degree) |
| Course Type | Elective |
| Course Coordinator | Assist.Prof. Rüçhan Melisa DENİZ ÖZGEN |
| Name of Lecturer(s) | |
| Assistant(s) | Res. Asst. Ahmed ŞENGİL ([email protected]) |
| Aim | This course aims to provide basic statistical techniques in order to collect, analyze and interpret data with emphasis on engineering applications. |
| Course 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. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| Construct and interpret graphical and/or numerical summaries of data. | 16, 9 | A |
| Distinguish between a population and a sample. | 14, 16, 9 | A, G |
| Construct confidence intervals for population characteristics | 12, 14, 16, 9 | A, E, G |
| Construct hypothesis tests for population characteristics. | 12, 16, 9 | A, E, G |
| Carry out correlation and regression analysis | 12, 16, 9 | A, E, G |
| Use statistical package SPSS to carry out the statistical procedures discussed during the semester. | 11, 9 | A, E |
| Teaching Methods: | 11: Demonstration Method, 12: Problem Solving Method, 14: Self Study Method, 16: Question - Answer Technique, 9: Lecture Method |
| Assessment Methods: | A: Traditional Written Exam, E: Homework, G: Quiz |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Introduction to Statistics and Data Analysis | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 1 |
| 2 | Sampling Distributions | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 8 |
| 3 | Sampling Distributions and Estimation | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 8 |
| 4 | Confidence Intervals-Single Population I | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 9 |
| 5 | Hypothesis Testing- Single Population I | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 10 |
| 6 | Confidence Intervals- Two Populations I | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 9 |
| 7 | Confidence Intervals- Two Populations II | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 9 |
| 8 | Hypothesis Testing- Two Populations I | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 10 |
| 9 | Hypothesis Testing- Two Populations II | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 10 |
| 10 | Introduction to Correlation and Regression Analysis | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 11 |
| 11 | Linear Regression Models | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 11 |
| 12 | Linear Regression Models | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 11 |
| 13 | Multiple Regression Models | Walpole, Myers, Myers, and Ye. "Probability and Statistics for Engineers and Scientists", Pearson, CHAPTER 12 |
| 14 | Advanced Topics in Multiple Regression Models | Lecture Notes |
| Resources |
| 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 |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | An ability to apply knowledge of mathematics, science, and engineering | X | |||||
| 2 | An ability to identify, formulate, and solve engineering problems | X | |||||
| 3 | An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability | ||||||
| 4 | An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice | X | |||||
| 5 | An ability to design and conduct experiments, as well as to analyze and interpret data | X | |||||
| 6 | An ability to function on multidisciplinary teams | X | |||||
| 7 | An ability to communicate effectively | ||||||
| 8 | A recognition of the need for, and an ability to engage in life-long learning | ||||||
| 9 | An understanding of professional and ethical responsibility | ||||||
| 10 | A knowledge of contemporary issues | ||||||
| 11 | The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context | ||||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 30 | |
| Rate of Final Exam to Success | 70 | |
| Total | 100 | |