İzmir Ekonomi Üniversitesi
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  • FACULTY OF ENGINEERING

    Department of Mechanical Engineering

    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
    Course Lecturer(s)
    Assistant(s)
    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.
    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.

     



    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 Midterm
    9 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.
    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
    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, Mathematics based physics, statistics and linear algebra and Mechanical 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 Mechanical Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

    -
    -
    -
    -
    -
    3

    To be able to design a thermal and mechanical 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 engineering applications.

    -
    -
    X
    -
    -
    5

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

    -
    -
    -
    -
    -
    6

    To be able to work efficiently in Mechanical 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 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 Mechanical 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 Mechanical Engineering.

    -
    -
    -
    -
    -

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

     


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