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      Department of Biomedical Engineering

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      MATH 236 | Course Introduction and Application Information

      Course Name
      Engineering Statistics
      Code
      Semester
      Theory
      (hour/week)
      Application/Lab
      (hour/week)
      Local Credits
      ECTS
      MATH 236
      Fall
      3
      0
      3
      6

      Prerequisites
        MATH 154 To attend the classes (To enrol for the course and get a grade other than NA or W)
      Course Language
      English
      Course Type
      Required
      Course Level
      First Cycle
      Mode of Delivery -
      Teaching Methods and Techniques of the Course Lecture / Presentation
      National Occupation Classification -
      Course Coordinator
      • Dr. Öğr. Üyesi Necla KOÇHAN
      Course Lecturer(s)
      • Dr. Öğr. Üyesi Necla KOÇHAN
      • Öğr. Gör. Dr. Gözde NAVRUZ
      Assistant(s)
      • Araş. Gör. Merve KAHRAMAN ARİMAN
      • Araş. Gör. Sıla Selenay KOÇ
      Course Objectives This course aims to provide students with the skills to collect, analyze and interpret statistical data.
      Learning Outcomes
      #
      Content
      PC Sub
      * Contribution Level
      1
      2
      3
      4
      5
      1analyze data via graphical and quantitative means.
      2define the fundamentals of statistical decision making.
      3use basic tools for the analysis and modeling of empirical relationships between variables.
      4investigate one and two sample estimation problems.
      5use hypothesis testings.
      6identify the dependent and the independent variables of the given data.
      7test whether the given variables are related depending on the number of independent variables.
      8apply simple linear regression analysis.
      Course Description This course focuses on sampling distributions, statistical estimation, hypothesis testing, simple and multiple linear regression. In addition, experimental design and applications of these methods to industrial systems engineering are discussed.
      Related Sustainable Development Goals

       



      Course Category

      Core Courses
      Major Area Courses
      Supportive Courses
      Media and Management Skills Courses
      Transferable Skill Courses

       

      WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

      Week Subjects Related Preparation Learning Outcome
      1 Introduction to Statistics and Data Analysis and Business Douglas C. Montgomery, Geroge C. Runger, “The Role of Statistics in Engineering”, Chap. 1 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 1-10.
      2 Introduction to Statistics and Data Analysis and Business, Data Description Douglas C. Montgomery, Geroge C. Runger, “Descriptive Statistics”, Chap. 6 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 198-218.
      3 Fundamental Sampling Distributions and Methods of Point Estimation Douglas C. Montgomery, Geroge C. Runger, “Point Estimation of Parameters and Sampling Distributions”, Chap. 7 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 235-258.
      4 Fundamental Sampling Distributions and Methods of Point Estimation Douglas C. Montgomery, Geroge C. Runger, “Point Estimation of Parameters and Sampling Distributions”, Chap. 7 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 235-258.
      5 One-Sample Estimation Problems Douglas C. Montgomery, Geroge C. Runger, “Statistical Intervals for a Single Sample”, Chap. 8 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 267-287.
      6 One-Sample Estimation Problems Douglas C. Montgomery, Geroge C. Runger, “Statistical Intervals for a Single Sample”, Chap. 8 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 267-287.
      7 One-Sample Tests of Hypotheses Douglas C. Montgomery, Geroge C. Runger, “Tests of Hypotheses for a Single Sample”, Chap. 9 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 301-352.
      8 Two-Sample Estimation Problems Douglas C. Montgomery, Geroge C. Runger, “Statistical Inference for Two Samples”, Chap. 10 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 369-385.
      9 Midterm Exam
      10 Two-Sample Estimation Problems Douglas C. Montgomery, Geroge C. Runger, “Statistical Inference for Two Samples”, Chap. 10 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 389-402.
      11 Two-Sample Tests of Hypotheses and Two-Sample Tests of Hypotheses Douglas C. Montgomery, Geroge C. Runger, “Tests of Hypotheses for Two Samples”, Chap. 10 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 301-352.
      12 Simple Linear Regression Douglas C. Montgomery, Geroge C. Runger, “Simple Linear Regression and Correlation”, Chap. 11 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 419-432.
      13 Hypothesis Tests in Simple Linear Regression, Confidence Intervals Douglas C. Montgomery, Geroge C. Runger, “Simple Linear Regression and Correlation”, Chap. 11 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 432-434.
      14 Coefficient of Determination Douglas C. Montgomery, Geroge C. Runger, “Simple Linear Regression and Correlation”, Chap. 11 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 437-438.
      15 Semester Review
      16 Final Exam

       

      Course Notes/Textbooks

      Douglas C. Montgomery, Geroge C. Runger, Applied Statistics and Probability for Engineers, 7th Ed. (United States of America: Wiley, 2018).

      ISBN: 978-1-119-40036-3

      Suggested Readings/Materials

      Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, Probability and Statistics for Engineers and Scientists, 9th Ed. (United States of America: Pearson, 2017).

      ISBN-13: 978-0321629111

       

      William Navidi, Statistics for Engineers and Scientists, 5th Ed. (United States of America: Mc-Graw Hill, 2019) 

      ISBN-13: 978-1260547887

       

      EVALUATION SYSTEM

      Semester Activities Number Weigthing LO 1 LO 2 LO 3 LO 4 LO 5 LO 6 LO 7 LO 8
      Participation
      Laboratory / Application
      Field Work
      Quizzes / Studio Critiques
      2
      10
      Portfolio
      Homework / Assignments
      Presentation / Jury
      Project
      Seminar / Workshop
      Oral Exams
      Midterm
      1
      40
      Final Exam
      1
      50
      Total

      Weighting of Semester Activities on the Final Grade
      3
      50
      Weighting of End-of-Semester Activities on the Final Grade
      1
      50
      Total

      ECTS / WORKLOAD TABLE

      Semester Activities Number Duration (Hours) Workload
      Theoretical Course Hours
      (Including exam week: 16 x total hours)
      16
      3
      48
      Laboratory / Application Hours
      (Including exam week: '.16.' x total hours)
      16
      0
      Study Hours Out of Class
      14
      3
      42
      Field Work
      0
      Quizzes / Studio Critiques
      2
      10
      20
      Portfolio
      0
      Homework / Assignments
      0
      Presentation / Jury
      0
      Project
      0
      Seminar / Workshop
      0
      Oral Exam
      0
      Midterms
      1
      30
      30
      Final Exam
      1
      40
      40
          Total
      180

       

      COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

      #
      PC Sub Program Competencies/Outcomes
      * Contribution Level
      1
      2
      3
      4
      5
      1

      To have adequate knowledge in Mathematics, Science and Biomedical Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems.

      -
      -
      X
      -
      -
      2

      To be able to identify, define, formulate, and solve complex Biomedical Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

      -
      -
      -
      -
      -
      3

      To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose.

      -
      -
      -
      -
      -
      4

      To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Biomedical Engineering applications.

      -
      -
      X
      -
      -
      5

      To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Biomedical Engineering research topics.

      -
      -
      -
      -
      -
      6

      To be able to work efficiently in Biomedical Engineering disciplinary and multi-disciplinary teams; to be able to work individually.

      -
      -
      -
      -
      -
      7

      To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions.

      -
      -
      -
      -
      -
      8

      To have knowledge about global and social impact of Biomedical Engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of engineering solutions.

      -
      -
      -
      -
      -
      9

      To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications.

      -
      -
      -
      -
      -
      10

      To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

      -
      -
      -
      -
      -
      11

      To be able to collect data in the area of Biomedical Engineering, and to be able to communicate with colleagues in a foreign language.

      -
      -
      -
      -
      -
      12

      To be able to speak a second foreign language at a medium level of fluency efficiently.

      -
      -
      -
      -
      -
      13

      To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Biomedical Engineering.

      -
      -
      -
      -
      -

      *1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest


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