The course aims to discuss importance topics in statistics in a mathematically rigorous way. The topics that will be discussed include sampling distributions and asymptotics, point and interval estimations, hypothesis testing, ANOVA and regression analysis. Implementations will be illustrated with R.
Special Topics in IE: Advanced statistics with R (IE 58005)
2022 Fall
Faculty of Engineering and Natural Sciences
Industrial Engineering(IE)
3
10
Semih Onur Sezer sezer@sabanciuniv.edu,
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English
Doctoral, Master
--
Formal lecture
Discussion based learning
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Programs\Type | Required | Core Elective | Area Elective |
Business Analytics - With Thesis | * | ||
Computer Science and Engineering - With Bachelor's Degree | * | ||
Computer Science and Engineering - With Master's Degree | * | ||
Computer Science and Engineering - With Thesis | * | ||
Cyber Security - With Bachelor's Degree | * | ||
Cyber Security - With Master's Degree | * | ||
Cyber Security - With Thesis | * | ||
Data Science - With Thesis | * | ||
Electronics Engineering and Computer Science - With Bachelor's Degree | * | ||
Electronics Engineering and Computer Science - With Master's Degree | * | ||
Electronics Engineering and Computer Science - With Thesis | * | ||
Electronics Engineering - With Bachelor's Degree | * | ||
Electronics Engineering - With Master's Degree | * | ||
Electronics Engineering - With Thesis | * | ||
Energy Technologies and Management-With Thesis | * | ||
Industrial Engineering - With Bachelor's Degree | * | ||
Industrial Engineering - With Master's Degree | * | ||
Industrial Engineering - With Thesis | * | ||
Leaders for Industry Biological Sciences and Bioengineering - Non Thesis | * | ||
Leaders for Industry Computer Science and Engineering - Non Thesis | * | ||
Leaders for Industry Electronics Engineering and Computer Science - Non Thesis | * | ||
Leaders for Industry Electronics Engineering - Non Thesis | * | ||
Leaders for Industry Industrial Engineering - Non Thesis | * | ||
Leaders for Industry Materials Science and Engineering - Non Thesis | * | ||
Leaders for Industry Mechatronics Engineering - Non Thesis | * | ||
Manufacturing Engineering - Non Thesis | * | ||
Manufacturing Engineering - With Bachelor's Degree | * | ||
Manufacturing Engineering - With Master's Degree | * | ||
Manufacturing Engineering - With Thesis | * | ||
Materials Science and Nano Engineering-(Pre:Materials Science and Engineering) | * | ||
Materials Science and Nano Engineering-(Pre:Materials Science and Engineering) | * | ||
Materials Science and Nano Engineering - With Thesis (Pre.Name: Materials Science and Engineering) | * | ||
Mathematics - With Bachelor's Degree | * | ||
Mathematics - With Master's Degree | * | ||
Mathematics - With Thesis | * | ||
Mechatronics Engineering - With Bachelor's Degree | * | ||
Mechatronics Engineering - With Master's Degree | * | ||
Mechatronics Engineering - With Thesis | * | ||
Molecular Biology, Genetics and Bioengineering (Prev. Name: Biological Sciences and Bioengineering) | * | ||
Molecular Biology, Genetics and Bioengineering-(Prev. Name: Biological Sciences and Bioengineering) | * | ||
Molecular Biology,Genetics and Bioengineering-With Thesis (Pre.Name:Biological Sciences and Bioeng.) | * | ||
Physics - Non Thesis | * | ||
Physics - With Bachelor's Degree | * | ||
Physics - With Master's Degree | * | ||
Physics - With Thesis | * |
CONTENT
OBJECTIVE
The course aims to discuss importance topics in statistics in a mathematically rigorous way. The topics that will be discussed include sampling distributions and asymptotics, point and interval estimations, hypothesis testing. Implementations will be illustrated with R.
Update Date:
ASSESSMENT METHODS and CRITERIA
Percentage (%) | |
Final | 55 |
Midterm | 45 |
RECOMENDED or REQUIRED READINGS
Readings |
Lecture notes prepared for the course by the instructor |