• Course Information
  • Course Title Code Semester Laboratory+Practice (Hour) Pool Type ECTS
    Experimental Methods and Data Analysis KMÜ504 FALL-SPRING 3+0 Faculty E 6
    Learning Outcomes
    1-They will be able to apply to basic statistical methods for experimental design, analyze and present the experimental results
    2-They will be able to calculate the experimental uncertainties in physical measurements.
    3-They will be able to comprehend temperature, pressure, flow rate and transmission and thermal properties such as mechanical measurement techniques
    4-They will be able to report and present the results of an experimental study.
  • ActivityPercentage


    NumberTime (Hours)Total Workload (hours)
    Course Duration (Weeks x Course Hours)14342
    Classroom study (Pre-study, practice)14570
    Short-Term Exams (exam + preparation) 0000
    Midterm exams (exam + preparation)3011515
    Laboratory 0000
    Final exam (exam + preparation) 5011515
    Other 0000
    Total Workload (hours)   170
    Total Workload (hours) / 30 (s)     5,67 ---- (6)
    ECTS Credit   6
  • Course Content
  • Week Topics Study Metarials
    1 Introduction and Basic Concepts
    2 Analysis of experimental data
    3 Analysis of experimental data
    4 Uncertainty analysis
    5 Pressure measurement
    6 Flow measurement
    7 Temperature measurement
    8 Midterm exams
    9 Midterm Exam
    10 Measurement of thermal and transport properties
    11 The experimental design
    12 The experimental design
    13 Report writing and presentation
    14 Report writing and presentation
    15 Data collection and processing
    Prerequisites -
    Language of Instruction Turkish
    Coordinator Associate. Prof. Dr. Barış Şimşek

    1-)Doçent Dr Barış Şimşek

    Assistants -
    Resources 1. Holman.J.P. (1986). Experimental methods for engineering: McGraw Hill. 2. Cebe M. ( 2006 ). Kimyada Veri Analizi Uygulamalı İstatistik: Nobel Kitapevi
    Supplementary Book -
    Goals Graduate studies in basic science and engineering science include experimental studies substantially. Course generally aims to plan an experimental study, analyze the experimental measurements and gain basic variables on measurement techniques and interpretation of results.
    Content Analysis of experimental data, Pressure, Flow and Temperature measurement, The experimental design, Report writing and presentation
  • Program Learning Outcomes
  • Program Learning Outcomes Level of Contribution
    1 To make scientific researches and reach the knowledge in depth; analyze interpret and apply the knowledge. 4
    2 To have knowledge about current technics, methods and their limitations applied in engineering. -
    3 To have the ability to define and practice the knowledge by using scientific methods and limited or restricted data and to use the knowledge from other disciplines. 4
    4 To have awareness about the new and developing implementations in engineering and to research and learn them when required. -
    5 To define and formulate problems concerning chemical engineering , to develop methods for solution and to apply innovative methods for solutions. -
    6 To develop new and/or original ideas and methods, to design complex systems and processes and to improve alternative/innovative solutions. -
    7 To design and apply theoretical, applied and simulative researches, to analyse and solve complicated problems encountered during these processes. -
    8 To lead in multidisciplinary teams, improve solutions in complex situation and to work independently and take responsibility. -
    9 To use English at least in European Language Portfolio B2 level for both oral and written skills. -
    10 To declare the results and processes of studies both orally and written in national and international platforms with a systematically and concisely manner. 4
    11 To have awareness about the social, enviromental, health, security and law perspectives and project management and career applications of engineering practices and restrictions of all these. -
    12 To regard social, scientific liabilities, and ethics during the collection, evaluation, and publication steps of data. 4
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