CANKIRI KARATEKIN UNIVERSITY Bologna Information System


  • Course Information
  • Course Title Code Semester Laboratory+Practice (Hour) Pool Type ECTS
    Probability Theorem and Statistics BİL212 SPRING 3+0 C 5
    Learning Outcomes
    1- define the basic concepts of statistics
    2-calculate descriptive statistics used to summarize the data set
    3-calculate probability by using probability functions of discrete and continuous random variables
    4- use sampling distribution
    5-apply the Central Limit Theorem
    6- create interval estimation for various parameters
    7- test hypothesis for various parameters
  • ECTS / WORKLOAD
  • ActivityPercentage

    (100)

    NumberTime (Hours)Total Workload (hours)
    Course Duration (Weeks x Course Hours)14342
    Classroom study (Pre-study, practice)14684
    Assignments0000
    Short-Term Exams (exam + preparation) 0000
    Midterm exams (exam + preparation)4011515
    Project0000
    Laboratory 0000
    Final exam (exam + preparation) 6012020
    Other 0000
    Total Workload (hours)   161
    Total Workload (hours) / 30 (s)     5,37 ---- (5)
    ECTS Credit   5
  • Course Content
  • Week Topics Study Metarials
    1 Statistical Science, Types of Statistical Applications, Basic Elements of Statistics, Data Types, Data Collection Methods K1-Chapter-1
    2 Measures of Central Tendency K1-Chapter-2
    3 Change Measures, Relative Status Measures K1-Chapter-2
    4 Sample Spaces and Events, Concepts of Junction and Intersection, Opposite Events Collection Rule and Mutual Discrete Events K2-Chapter-3
    5 Discrete random variables, Probability Distributions K2-Chapter-3
    6 Continuous Random Variables, Probability Density Function K2-Chapter-3
    7 Discrete Uniform Distribution, Bernoulli Distribution, Binomial Distribution, Hypergeometric Distribution, Poisson Distribution K3-Chapter-4
    8 Normal Distribution, Approximation of Binomial Distribution to Normal Distribution, Exponential Distribution K3-Chapter-4
    9 Example Problem Solving K3-Chapter-4
    10 What is sampling distribution, Central Limit Theorem K3-Chapter-5
    11 Large and Small Sample Range Estimation and Hypothesis Testing for a Population Mean K2-Chapter-6
    12 Large Sample Range Estimation for Two Population Mean Large Sample Range Estimation for a Population Rate Large Sample Range Estimation for a Population K2-Chapter-6
    13 Large Sample Range Estimation for Two Population Ratio Large Sample Range Estimation for Two Population Variance Hypothesis Tests K2-Chapter-6
    14 Chi-square test K2-Chapter-7
    Prerequisites -
    Language of Instruction Turkish
    Responsible Assist. Prof. Dr. Efehan Ulaş
    Instructors -
    Assistants -
    Resources K1- Williem W. Hines, Douglas C. Monthgomery, Probability and Statistics in Engineering and Management Science. Third Edition, 1990. K2-DeGroot, Morris H., and Mark J. Schervish. Probability and Statistics. 3rd ed. Boston, MA: Addison-Wesley, 2002. ISBN: 0201524880. K3- Walpole R.E., Myers R.H., Myers Sh. L., Ye K. Probability and Statistics or Engineers and Scientists Prentice Hall, 7/E, 2002. K4- Akdeniz F., Olasılık ve İstatistik, Nobel Kitabevi, 13. Baskı, 2007.
    Supplementary Book -
    Goals to teach the basic concepts of probability and statistics.
    Content Statistical Science, Types of Statistical Applications, Basic Elements of Statistics, Data Types, Data Collection Methods, Measures of Central Tendency, Change Measures, Relative Status Measures, Sample Spaces and Events, Concepts of Junction and Intersection, Opposite Events Collection Rule and Mutual Discrete Events, Discrete random variables, Probability Distributions, Continuous Random Variables, Probability Density Function, Discrete Uniform Distribution, Bernoulli Distribution, Binomial Distribution, Hypergeometric Distribution, Poisson Distribution, Normal Distribution, Approximation of Binomial Distribution to Normal Distribution, Exponential Distribution, What is sampling distribution, Central Limit Theorem, Large and Small Sample Range Estimation and Hypothesis Testing for a Population Mean, Large Sample Range Estimation for Two Population Mean Large Sample Range Estimation for a Population Rate Large Sample Range Estimation for a Population, Large Sample Range Estimation for Two Population Ratio Large Sample Range Estimation for Two Population Variance Hypothesis Tests, Chi-square test
  • Program Learning Outcomes
  • Program Learning Outcomes Level of Contribution
    1 To be able to apply mathematics, science and engineering theories and principles to Computer Engineering problems. 5
    2 To have the ability to define, model, and solve problems related to Computer Engineering. 4
    3 To be able to design and conduct experiments, as well as to analyze and interpret data. 2
    4 To be able to design and analyze a process for a specific purpose within technical and economical limitations. -
    5 To be able to use modern techniques and calculation tools required for engineering applications. -
    6 To have the awareness of professional liabilities and ethics. -
    7 To be able to get involved in interdisciplined and multidisciplined team work. -
    8 To be able to declare his/her opinions orally or written in a clear, concise and brief manner. -
    9 To improve him/herself by following the developments in science, technology, modern issues, and know the importance of lifelong learning. -
    10 To be able to evaluate engineering solutions for the global and social problems especially for the health, safety, and environmental problems. -
    11 To have knowledge about of contemporary issues. -
    Çankırı Karatekin Üniversitesi  Bilgi İşlem Daire Başkanlığı  @   2017 - Webmaster