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| Course Description |
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| Course Name |
: |
Introduction To Probability |
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| Course Code |
: |
İSB103 |
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| Course Type |
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Compulsory |
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| Level of Course |
: |
First Cycle |
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| Year of Study |
: |
1 |
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| Course Semester |
: |
Fall (16 Weeks) |
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| ECTS |
: |
6 |
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| Name of Lecturer(s) |
: |
Prof.Dr. SELAHATTİN KAÇIRANLAR
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| Learning Outcomes of the Course |
: |
Explains Sample spaces, Sample points and Counting Rules
Solve the problems of permutations, combinations, and be able fragmentation unordered
Uses probability of an event, the Rules of Probability Probability Axioms
Applies conditional Probability, Independent events, Bayes´ Theorem
Learn the concept of a random variable and distribution of a random variable
Describe the expected value of a random variable, the variance and the properties
Use moments, skewness and kurtosis in a range, the concepts of inequality Chebyshew
Learn bernoulli, binomial, polynomial, geometric, negative binomial, some discrete distributions
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| Mode of Delivery |
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Face-to-Face |
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| Prerequisites and Co-Prerequisites |
: |
None |
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| Recommended Optional Programme Components |
: |
None |
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| Aim(s) of Course |
: |
This course aims to help students acquire a powerful background on probability, conditional probability, dependence, independence, random variables, distributions. |
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| Course Contents |
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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 |
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| Language of Instruction |
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Turkish |
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| Work Place |
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Faculty of Arts and Sciences Annex Classrooms |
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Course Outline /Schedule (Weekly) Planned Learning Activities |
| Week | Subject | Student's Preliminary Work | Learning Activities and Teaching Methods |
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1 |
The concept of clusters, Sample space, sample point, event counting rules sample points |
Source reading |
Lecture, discussion and problem-solving |
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2 |
Permutations, circular permutations, combinations, Pascal convention, repeated combinations |
Source reading |
Lecture, discussion and problem-solving |
|
3 |
All objects that are not different from each other permutations, ordered and unordered disruptions, Binomial Theorem |
Source reading |
Lecture, discussion and problem-solving |
|
4 |
Introduction to Probability: the probability of an event and the probability axioms, some of the rules of probability |
Source reading |
Lecture, discussion and problem-solving |
|
5 |
Introduction to Probability: the probability of an event and the probability axioms, some of the rules of probability |
Source reading |
Lecture, discussion and problem-solving |
|
6 |
Independent events, Bayes´ theorem and its applications |
Source reading |
Lecture, discussion and problem-solving |
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7 |
Random variables, distribution of discrete random variables probability , Probability function and drawing , distribution function and drawing |
Source reading |
Lecture, discussion and problem-solving |
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8 |
mid-term exam |
Rewview the topics discussed in the lecture notes and sources |
Written exam |
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9 |
The distribution of continuous random variables, probability density function and drawing, distribution function and drawing |
Source reading |
Lecture, discussion and problem-solving |
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10 |
Two-dimensional random variables, Joint probability function, Joint probability density function |
Source reading |
Lecture, discussion and problem-solving |
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11 |
The expected value of a random variable, the variance and their properties, Chebyshev´s theorem |
Source reading |
Lecture, discussion and problem-solving |
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12 |
Bernoulli distribution, binomial distribution, a multinomial distribution |
Source reading |
Lecture, discussion and problem-solving |
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13 |
Geometric, negative binomial distribution, Hypergeometric distribution |
Source reading |
Lecture, discussion and problem-solving |
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14 |
Poisson distribution, uniform distribution, Comparison of Discrete Distributions |
Source reading |
Lecture, discussion and problem-solving |
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15 |
input continuous distributions and problem-solving |
Source reading |
Lecture, discussion and problem-solving |
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16/17 |
Final exam |
Rewview the topics discussed in the lecture notes and sources |
Written exam |
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Required Course Resources |
| Resource Type | Resource Name |
| Recommended Course Material(s) |
 Fikri Akdeniz (2009), Olasılık ve İstatistik, Nobel Kitabevi, Adana
DeGroot,MH and Schervish, MJ (2002), Probability and Statistics, Third edition, Addison Wesley
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| |
| Required Course Material(s) | |
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Assessment Methods and Assessment Criteria |
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Semester/Year Assessments |
Number |
Contribution Percentage |
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Mid-term Exams (Written, Oral, etc.) |
1 |
80 |
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Homeworks/Projects/Others |
6 |
20 |
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Total |
100 |
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Rate of Semester/Year Assessments to Success |
40 |
| |
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Final Assessments
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100 |
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Rate of Final Assessments to Success
|
60 |
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Total |
100 |
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| Contribution of the Course to Key Learning Outcomes |
| # | Key Learning Outcome | Contribution* |
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1 |
Utilize computer systems and softwares |
0 |
|
2 |
Apply the statistical analyze methods |
1 |
|
3 |
Make statistical inference(estimation, hypothesis tests etc.) |
0 |
|
4 |
Generate solutions for the problems in other disciplines by using statistical techniques |
2 |
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5 |
Discover the visual, database and web programming techniques and posses the ability of writing programme |
0 |
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6 |
Construct a model and analyze it by using statistical packages |
0 |
|
7 |
Distinguish the difference between the statistical methods |
2 |
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8 |
Be aware of the interaction between the disciplines related to statistics |
1 |
|
9 |
Make oral and visual presentation for the results of statistical methods |
0 |
|
10 |
Have capability on effective and productive work in a group and individually |
1 |
|
11 |
Develop scientific and ethical values in the fields of statistics-and scientific data collection |
4 |
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12 |
Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics |
5 |
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13 |
Emphasize the importance of Statistics in life |
4 |
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14 |
Define basic principles and concepts in the field of Law and Economics |
0 |
|
15 |
Produce numeric and statistical solutions in order to overcome the problems |
4 |
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16 |
Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events |
5 |
|
17 |
Use proper methods and techniques to gather and/or to arrange the data |
3 |
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18 |
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 |
0 |
| * Contribution levels are between 0 (not) and 5 (maximum). |
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| Student Workload - ECTS |
| Works | Number | Time (Hour) | Total Workload (Hour) |
| Course Related Works |
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Class Time (Exam weeks are excluded) |
14 |
4 |
56 |
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Out of Class Study (Preliminary Work, Practice) |
14 |
4 |
56 |
| Assesment Related Works |
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Homeworks, Projects, Others |
6 |
2 |
12 |
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Mid-term Exams (Written, Oral, etc.) |
1 |
15 |
15 |
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Final Exam |
1 |
20 |
20 |
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Total Workload: | 159 |
| Total Workload / 25 (h): | 6.36 |
| ECTS Credit: | 6 |
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