Course Information
SemesterCourse Unit CodeCourse Unit TitleL+PCreditNumber of ECTS Credits
6MATH332PROBABILITY STATISTICS4+258

Course Details
Language of Instruction English
Level of Course Unit First Cycle
Department / Program MATHEMATICS
Mode of Delivery Face to Face
Type of Course Unit Compulsory
Objectives of the Course The course aims at introducing the fundamental concepts of probability and statistics, and how to use them in real life problems through computer applications . The students will be made familiar with the basics of a statistical computer language. Basic objects of the study in probability such as sample spaces, random variables will be introduced. Special emphasis will be placed upon distributions frequently encountered in applications to enable the students to apply the methods learned in the course. Statistical methods necessary to analyze the data produced from the real life and make inferences will be presented. Students will implement these methods in computer lab sessions held weekly.
Course Content Basics of statistical computer languages, Random Variables, Mean, Variance, Binomial and Poisson distributions, Continuous distributions, Central Limit Theorem and applications, Exploratory data analysis, Point Estimation, Interval Estimation, Hypothesis testing, Linear and Logistics Regression, Analysis of Variance.
Course Methods and Techniques
Prerequisites and co-requisities None
Course Coordinator Prof.Dr. Oğuz Yılmaz
Name of Lecturers Prof.Dr. OĞUZ YILMAZ
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Peter Dalgaard, Introductory statistics with R, Springer
Suggested textbooks: M.D. Ugarte, A.F. Militino, A.T. Arnholt, Probability and Statistics with R, CRC Press, Larry Wasserman, All of Statistics, Springer
Dersi veren hocanın uhdesindedir.
2 vize 1 final

Course Category

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Midterm exams 2 % 40
Quizzes 0 % 0
Homeworks 0 % 0
Other activities 0 % 0
Laboratory works 5 % 20
Projects 0 % 0
Final examination 1 % 40
Total
8
% 100

ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Weekly Course Time 14 3 42
Outside Activities About Course (Attendance, Presentation, Midterm exam,Final exam, Quiz etc.) 14 4 56
Application (Homework, Reading, Self Study etc.) 8 6 48
Laboratory 14 2 28
Exams and Exam Preparations 3 25 75
Total Work Load   Number of ECTS Credits 8 249

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 understand the general concepts of probability and statistics with computer implementations
2 Understand the common probability distributions and implement them with computing applications
3 Computes the confidence intervals, means, standard deviations
4 Analyze the real world data by using the statistical methods introduced in the course with computers
5 Can study further the concepts of statistics and probability in graduate level


Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Basics of statistical computer languages Ref.1 Ch 1
2 Probability and Random Variables Ref.1. Ch 3
3 Mean, Variance Ref.1 Ch 3
4 Binomial distribution, Poisson distribution Ref.1. Ch 4
5 Continuous distributions Ref.1. Ch 4
6 Central limit theorem, applications Ref.1. Ch 5
7 Exploratory data analysis Ref.1. Ch 6
8 Point Estimation Ref.1 Ch7
9 Interval Estimation Ref.1. Ch 8
10 Hypothesis testing Ref.1. Ch 9
11 Hypothesis testing Ref.1. Ch 9
12 Linear Regression Ref.1. Ch 12
13 Logistics regression Ref.1. Ch 12
14 Analysis of Variance Ref.1. Ch 12


Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14
All 5 5 4 5 4 5 4 5 4 4 4 4 4
C1 5 5 4 5 4 5 4 5 4 4 4 4 4
C2 5 5 4 5 4 5 4 5 4 4 4 4 4
C3 5 5 4 5 4 5 4 5 4 4 4 4 4
C4 5 5 4 5 4 5 4 5 4 4 4 4 4
C5 5 5 4 5 4 5 4 5 4 4 4 4 4

Contribution: 0: Null 1:Slight 2:Moderate 3:Significant 4:Very Significant


https://obs.iyte.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=254373&lang=en