COURSE UNIT TITLE

: PROBLEM BASED LEARNING I

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IST 2015 PROBLEM BASED LEARNING I COMPULSORY 2 0 0 4

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR TUĞBA YILDIZ

Offered to

Statistics
Statistics(Evening)

Course Objective

This course provides generating research questions, discussion on the choice of appropriate mathematical statistical approaches and case studies: application of mathematical statistical methods to various fields. Discussion and evaluation of previously done studies from the literature.

Learning Outcomes of the Course Unit

1   Demonstrate basic principles of probability, and sample space.
2   Apply the conditional probability, Bayes rule.
3   Demonstrate the properties of probability distributions and cumulative distribution functions of the discrete and continuous random variables.
4   Describe the basic discrete distributions (Bernoulli, Binomial, Geometric, Negative Binomial, Hypergeometric, and Poisson) with properties
5   Describe the basic continuous distributions (Uniform, Normal, Standard normal, Exponential, Gamma) with properties
6   Calculate moments and moment generating functions of random variables.
7   Calculate basic two-variable statistics (covariance, correlation) usingthe joint distributions, conditional distributions
8   Obtain the distributions of the functions of random variables

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Definition of probability
2 Applications of probability concepts and properties
3 Conditional probability and independence concepts
4 Random Variables, Discrete random variables, Probability distribution and Cumulative distribution function
5 Continuous random variables, Probability distribution and Cumulative distribution function
6 Expected Value and its Properties, Moments and Moment Generating Functions
7 Special Discrete Distributions (Bernoulli, Binomial, Geometric, Negative Binomial, Hypergeometric, and Poisson)
8 Midterm exam
9 Special Continuous Distributions
10 Joint probability distributions, Marginal distributions
11 Conditional Distributions, Independent Random Variables
12 Expected values of bivariate distributions, conditional expected value, conditional variance and its properties.
13 Covariance and Correlation
14 Methods for distributions of functions of random variables (CDF and Transformation Methods)

Recomended or Required Reading

Textbook(s):
L. J. Bain and M. Engelhardt, Introduction to Probability and Mathematical Statistics, 2nd Edition, Duxbury, 1992.
Supplementary Book(s):
1. R. J. Larsen and M. L. Marx, An Introduction to Mathematical Statistics and Its Applications, 4th Edition, Prentice Hall.
2. I. Miller and M. Miller, John E. Freund's Mathematical Statistics with Applications, 7 edition Prentice Hall, 2003.H. Taha, Operations Research, McGraw Hill, 7th edition, 2003

Planned Learning Activities and Teaching Methods

Problem based learning, class discussion.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.40 + FIN * 0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + FIN * 0.60


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Since this is an active learning system based lecture, the grades will be evaluated with 40% midterm+60% final exam. Class participation is an important criterion for evaluating the student's achievements.

Language of Instruction

Turkish

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and Quiz-final exam dates-times must be followed. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 15 2 30
Preparation for midterm exam 1 25 25
Preparation for final exam 1 30 30
Preparation for quiz etc. 1 6 6
Midterm 1 2 2
Final 1 2 2
Quiz etc. 1 1 1
TOTAL WORKLOAD (hours) 96

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.15554
LO.25554
LO.35554
LO.45554
LO.55554
LO.65554
LO.75554
LO.85554