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HU Credits:
6
Degree/Cycle:
1st degree (Bachelor)
Responsible Department:
Statistics
Semester:
1st Semester
Teaching Languages:
Hebrew
Campus:
E. Safra
Course/Module Coordinator:
Pavel Chigansky
Coordinator Office Hours:
Sunday, 14:00
Teaching Staff:
Dr. Or Zuk
Dr. Pavel Chigansky
Yaniv Tenzer
Course/Module description:
The course will present the fundamentals of probability, the mathematical framework for handling scenarios of uncertainty or randomness. The final part of the course will give an introductory taste of statistics.
Course/Module aims:
To develop the basic tools of probability in a mathematically precise yet intuitive manner, to demonstrate the application of these tools on varied problems, to develop "probabilistic thinking", to develop and implement introductory tools in statistics.
Learning outcomes - On successful completion of this module, students should be able to:
Use the tools of probability to solve discrete and continuous probabilistic problems, prove simple (new) probabilistic claims, implement probabilistic thinking, cope with elementary statistical problems
Attendance requirements(%):
0
Teaching arrangement and method of instruction:
Teaching relies on doing 5 learning activities each week:
1. Watching the pre-recorded online lectures that present the basic learning material. (2 hours)
2. Computerized assessments that check basic comprehension of the content of the online lectures.
3. Class lectures. During the first hour of the lecture the teacher will use examples in order to summarize the topics of the week. In the second hour he will deal with the mathematical background and concepts that are required for solving exercises and he will provide background for the subsequent week's lecture. This component does not substitute the requirement for watching the online lectures. (2 hours of lecture)
4. An exercise with a teaching assistant. The teaching assistant will present a series of problems and solve them in class. (2 hours of exercise.)
5. An active exercise workshop. In this workshop the students will be required to do an exercise. The structure and level of difficulty of the exercise will parallel the exams. The material for the exercise will include the material up to the week that precedes the workshop (including). The exercise will be handed to the students at the workshop location. Two hours will be allocated for completing the exercise. Students can solve the exercise at the workshop location independently or in groups of up to 3 students each. Teaching assistants will be available at the spot to help and to answer questions. Each student will submit his exercise form by the end of the two hours. Exercises that were completed in a group will be submitted jointly by all group members, so that each member in the group submit his personal form as part of his group. All the forms of a given group will be attached to each other. Exercises that were submitted individually will be scored individually. A representative form will be scored for each group. (2 hours of workshop activity)
Course/Module Content:
Probability: the axiomatic approach, discrete and continuous probabilistic spaces, conditional probability, independence, complete probability formula and Bayes rule, discrete random variables, functions of random variables, expectation and variance, joint probability conditioning and independence of random variables, continuous random variables, cumulative distribution function, covariance and correlation, conditional expectation and variance, moment generating functions, probabilistic inequalities and the weak law of large numbers, convergence concepts and the central limit theorem. A brief introduction to statistics: population and samples, estimation, hypothesis testing.
Required Reading:
Students are required to watch the video clips before the lecture.
Additional Reading Material:
Introduction to Probability by Dimitri Bertsekas and John
Tsitsiklis
Course/Module evaluation:
End of year written/oral examination 55 %
Presentation 0 %
Participation in Tutorials 0 %
Project work 0 %
Assignments 20 %
Reports 0 %
Research project 0 %
Quizzes 20 %
Other 5 %
Additional information:
1. Students are required to submit the computerized assessment (activity 2 in methods of instruction). The weight of the computerized assessment in the final grade is 5 points.
2. The weight of the workshop in the final grade is 20 points. An exercise that was submitted will be scored. An exercise that was not submitted will get a 0 score. The average score of the exercises will be based on the 10 best scores.
3. There will be 2 midterms. The weight of each in the final grade will be 10 points.
4. In principle, the computerized assessment and the workshop exercise must be submitted in time. If a student could not submit either in a given week for a justified reason and obtained an approval for that then then the average score will be computed on the basis of a smaller number of exercises in accordance to the number of weeks that were justifiably missing.
5. The exam grade will replace the 10% of the first quiz if the grade is higher.
6. The exam grade will replace the 10% of the second quiz if the second quiz is missed for a justified reason (e.g. army reserve). If the second quiz is missed for an unjustified reason, the quiz grade will be 0.
7. The exam grade will be 100% of the final grade in case of a failing grade.
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