Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
4MIS 222Probability and Statistics II3+0+03528.07.2021

 
Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program Management Information Systems (English)
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course to teach basic concepts of probability and statistics
Course Content Pair of random variables, joint probability distributions, point estimation, hypotheses testing
Course Methods and Techniques
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Asist Prof.Dr. Çiğdem TOPÇU GÜLÖKSÜZ
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Hogg R.V., Craig., McKean J.W. Introduction to Mathematical Statistics, 7th Edition, Pearson Education Inc.,2012.
Rohatgi, V.K., A. K. Md. Ehsanes Saleh. An Introduction to Probability and Statistics, 3rd Edition, John Wiley, 2015.
Ross, S. M. Introduction to Probability Models, 10th Edition, Elsevier, 2010.
Course Notes Lecturing, discussion, problem solving; Face to face/ distance learning/hybrid

Course Category
Mathematics and Basic Sciences %100

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
Mid-terms 1 % 40
Final examination 1 % 60
Total
2
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 3 42
Hours for off-the-c.r.stud 14 5 70
Assignments 14 2 28
Mid-terms 1 2 2
Final examination 1 2 2
Total Work Load   Number of ECTS Credits 5 144

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 understand probability distributions for bivariate random variables
2 develop probability models for the joint behavior of several random variables
3 know estimation procedures
4 distinguish point estimation and interval estimation
5 construction and testing hypotheses related to mean, ratio and variance based on single and two samples

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Bivariate discrete random variables, joint probability function, marginal probability functions and the relationship between them
2 conditional distributions, expected value, variance, covariance, correlation for discrete case
3 Bivariate continuous random variables, joint probability density function, marginal probability functions and the relationship between them
4 conditional distributions, expected value, variance, covariance, correlation for continuous case
5 A short brief of more than two variables
6 Exercises
7 Midterm Exam
8 Basic concepts of point estimation
9 Methods of point estimation
10 Properties of confidence intervals, confidence interval for population mean and variance
11 Tests of Hypotheses based on single sample, test procedures
12 Tests about population mean, variance and ratio
13 Tests of Hypotheses based on two sample, test procedures
14 Test for difference between two population means,variances, ratios
15 Supplementary exercises
16 Final Exam

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
C1 5 1 1 2 1 5 1 4 5 2 5
C2 5 1 1 2 1 5 1 4 5 2 5
C3 5 1 1 2 1 5 1 4 5 2 5
C4 5 1 1 2 1 5 1 4 5 2 5
C5 5 1 1 2 1 5 1 4 5 2 5

  Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

  
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