CANKIRI KARATEKIN UNIVERSITY Bologna Information System


  • Course Information
  • Course Title Code Semester Laboratory+Practice (Hour) Pool Type ECTS
    Introduction to Probability and Statistics İST268 SPRING 3+0 S 3
    Learning Outcomes
    1-Explains the relation between sets and sample space.
    2-Defines the basic concepts of probability.
    3-Learn density and distribution functions of random variables and apply them to real problems.
  • ECTS / WORKLOAD
  • ActivityPercentage

    (100)

    NumberTime (Hours)Total Workload (hours)
    Course Duration (Weeks x Course Hours)14342
    Classroom study (Pre-study, practice)14228
    Assignments0000
    Short-Term Exams (exam + preparation) 0000
    Midterm exams (exam + preparation)4011010
    Project0000
    Laboratory 0000
    Final exam (exam + preparation) 6012020
    0000
    Total Workload (hours)   100
    Total Workload (hours) / 30 (s)     3,33 ---- (3)
    ECTS Credit   3
  • Course Content
  • Week Topics Study Metarials
    1 Introduction to clusters, set operations, classes and elements. R1, Section 1
    2 Experiment with random outcome, sample point, sample spaces and events. R1, Section 2
    3 Permutation R1, Section 3
    4 Combination, Binom`s theorem R1, Section 4
    5 Probability measure, probability space and some examples of probability spaces R1, Section 5
    6 Discrete and continuous sample spaces and geometric probability R1, Section 6
    7 Conditional probability, total probability formula, Bayes rule and independence of events. R1, Section 7
    8 The concept of random variable R1, Section 8
    9 Distribution of discrete random variable R1, Section 9
    10 Distribution of continuous random variable R1, Section 10
    11 Expected value, variance and application of random variable R1, Section 11
    12 Two dimensional random variables and probability functions R1, Section 12
    13 Conditional probability function, marginal functions, R1, Section 13
    14 Conditional expected value and conditional variance, Distribution function R1, Section 14
    Prerequisites -
    Language of Instruction Turkish
    Responsible Assoc. Prof. Efehan Ulas
    Instructors -
    Assistants -
    Resources R1. Ders Notu
    Supplementary Book SR1. Freund, J. E., Miller, I., & Miller, M. (2007). Matematiksel İstatistik,(çev. Ümit Şenesen), 6. Baskı, Literatür Yayıncılık, İstanbul. SR2. Akdeniz, F. (2006). Olasılık ve İstatistik, Nobel Kitabevi, 18. Baskı, Adana. SR3. Sağlam, V. (2017). Olasılığa Giriş, Seçkin yayınevi.
    Goals Learns the fundamental concepts of affine and projective geometries and understand the related transformations.
    Content Random variable, sample space, selection rules, sampling, binomial theorem, expected value, variance.
  • Program Learning Outcomes
  • Program Learning Outcomes Level of Contribution
    1 To have informations about conceptional, theoretical and applied statistics and and associates the concepts with each other. 2
    2 To collect, save and arrange the statistical data, builds the proper tables and graphics to summarize data 3
    3 To analyse the data, to able to determine suitable statistical method, to make more efficient inferences and forecasts for the future 2
    4 To design and analyse an experiment and interpreting the results 2
    5 To have the knowlegde about Mathematics and Economics -
    6 To define statistics problems and develop suggestions by using statistical survey. -
    7 To use the profiency knowlegde on interdiscipliner studies -
    8 To have the ability of planing, managing and reporting of a project -
    9 To use computer softwares and programmes for statistics methods. -
    10 To have the ability of analythical thinking -
    11 To have the individual study skills and be capable of independent decision-making -
    12 To have the qualifications required for team work -
    13 To follow developments in statistics field by using a foreign language and can be connected with their colleagues. -
    14 To have scientific and ethnical values in data collection and interpretation in statistics dicipline. -
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