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 | Required |
Course Coordinator | Assoc.Prof. Melis Almula KARADAYI |
Name of Lecturer(s) | Assoc.Prof. Melis Almula KARADAYI |
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 | Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems. | X | |||||
2 | Ability to formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | X | |||||
3 | Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. | ||||||
4 | Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively. | X | |||||
5 | Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions. | X | |||||
6 | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | X | |||||
7 | Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | ||||||
8 | Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. | X | |||||
9 | Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices. | ||||||
10 | Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development. | ||||||
11 | Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions. |
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 | Required |
Course Coordinator | Assoc.Prof. Melis Almula KARADAYI |
Name of Lecturer(s) | Assoc.Prof. Melis Almula KARADAYI |
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 | Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems. | X | |||||
2 | Ability to formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | X | |||||
3 | Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. | ||||||
4 | Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively. | X | |||||
5 | Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions. | X | |||||
6 | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | X | |||||
7 | Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | ||||||
8 | Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. | X | |||||
9 | Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices. | ||||||
10 | Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development. | ||||||
11 | Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions. |
Assessment Methods
Contribution Level | Absolute Evaluation | |
Rate of Midterm Exam to Success | 30 | |
Rate of Final Exam to Success | 70 | |
Total | 100 |