COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Introduction to Probability * ISB   103 1 4 4 6

Prerequisites and co-requisites
Recommended Optional Programme Components None

Language of Instruction Turkish
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Prof. Dr. Selahattin KAÇIRANLAR
Instructors
Prof. Dr.SELAHATTİN KAÇIRANLAR1. Öğretim Grup:A
Prof. Dr.SELAHATTİN KAÇIRANLAR2. Öğretim Grup:A
 
Assistants
Goals
This course aims to help students acquire a powerful background on probability, conditional probability, dependence, independence, random variables, distributions.
Content
Students will gain competence on sample space, events. Basic combinatorial probability, conditional probability. Bayes’ theorem, dependence, independence, random variables, distributions, Bernoilli, Binomial, Poisson distributions, Gamma, normal, exponential, chi-square distributions, expectation, marginal distributions

Learning Outcomes
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Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics
X
2
Emphasize the importance of Statistics in life
X
3
Define basic principles and concepts in the field of Law and Economics
4
Produce numeric and statistical solutions in order to overcome the problems
X
5
Use proper methods and techniques to gather and/or to arrange the data
X
6
Utilize computer systems and softwares
X
7
Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events
X
8
Apply the statistical analyze methods
X
9
Make statistical inference(estimation, hypothesis tests etc.)
X
10
Generate solutions for the problems in other disciplines by using statistical techniques
X
11
Discover the visual, database and web programming techniques and posses the ability of writing programme
12
Construct a model and analyze it by using statistical packages
13
Distinguish the difference between the statistical methods
X
14
Be aware of the interaction between the disciplines related to statistics
X
15
Make oral and visual presentation for the results of statistical methods
X
16
Have capability on effective and productive work in a group and individually
X
17
Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs
X
18
Develop scientific and ethical values in the fields of statistics-and scientific data collection
X

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 The concept of clusters, Sample space, sample point, event counting rules sample points Source reading
2 Permutations, circular permutations, combinations, Pascal convention, repeated combinations Source reading
3 All objects that are not different from each other permutations, ordered and unordered disruptions, Binomial Theorem Source reading
4 Introduction to Probability: the probability of an event and the probability axioms, some of the rules of probability Source reading
5 Introduction to Probability: the probability of an event and the probability axioms, some of the rules of probability Source reading
6 Independent events, Bayes theorem and its applications Source reading
7 Random variables, distribution of discrete random variables probability , Probability function and drawing , distribution function and drawing Source reading
8 Midterm exam Review the topics discussed in the lecture notes and sources
9 The distribution of continuous random variables, probability density function and drawing, distribution function and drawing Source reading
10 Two-dimensional random variables, Joint probability function, Joint probability density function Source reading
11 The expected value of a random variable, the variance and their properties, Chebyshevs theorem Source reading
12 Bernoulli distribution, binomial distribution, a multinomial distribution Source reading
13 Geometric, negative binomial distribution, Hypergeometric distribution Source reading
14 Poisson distribution, uniform distribution, Comparison of Discrete Distributions Source reading
15 input continuous distributions and problem-solving Source reading
16-17 Final exam Review the topics discussed in the lecture notes and sources

Recommended or Required Reading
Textbook
Additional Resources