Probability and Statistics I (MATH291) Course Detail

Course Name	Course Code	Season	Lecture Hours	Application Hours	Lab Hours	Credit	ECTS
Probability and Statistics I	MATH291		3	0	0	3	5

Pre-requisite Course(s)
None

Course Language	English
Course Type	N/A
Course Level	Bachelor’s Degree (First Cycle)
Mode of Delivery	Face To Face
Learning and Teaching Strategies	Lecture, Question and Answer, Problem Solving.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives	In addition to some tools for classification, summarization and making sense of data, to provide students with basic probability knowledge and certain probability distributions
Course Learning Outcomes	The students who succeeded in this course; Upon completing of the course, students are expected to: 1- learn how to organize a set of data 2- be able to summarize the data by using the measures of central tendency and dispersion 3- calculate the probability with the assistance of basic concept of probability including some counting techniques, permutations and combinations 4- have the ability to use conditional probability, Bayesian approach and statistically independency within probability problems 5- be able to calculate the mean and standard deviation with expected value concept by understanding the difference between discrete and continuous random variables, 6- have the ability to use some probability distributions such as binomial and normal probability functions.
Course Content	Basic definitions, tables and graphs, central tendency measures, central dispersion measures, probability concept, conditional probability, Bayesian approach, random variables, expected value, binomial and normal distributions.

Weekly Subjects and Releated Preparation Studies

Week	Subjects	Preparation
1	Basic Definitions, Frequency Distributions	pp. 3-5
2	Relative, Cumulative, Cumulative Relative Frequency Distributions, Graphs, Stem and Leaf Display	pp. 24-28
3	Central Tendency Measures; Mean, Median and Mode for Unclassified and Classified Data	pp. 73-76
4	Central Dispersion Measures; Variance, Standard Deviation, Coefficient of Variation, Chebyshev Theorem	pp. 93-100
5	Probability Concept, Random Event-Experiment, Sample Space,	pp. 127-130
6	Classical / Postrerior Probability Definitions , Rule of Counting; Permutation and Combination, Multiplication Rule	pp. 135-137
7	Midterm Exam
8	Venn Diagrams, Contingency Table, Conditional Probability	pp. 138-140
9	Bayesian Approach, Statistical Indpendency	pp. 142-145
10	Random Variables, Probability Function	pp. 147-150
11	Expected Value and Its Properties, Mean and Standard Deviation	pp. 155-157
12	Binomial Distribution	pp. 167-168
13	Normal Distribution, Standard Normal Variable, Z table	pp. 182-185
14	Problems on Normal Distribution and Vice-Verse Usage of Z table (Cut-off value )	pp. 199-205
15	Review
16	Final Exam

Sources

Course Book	1. D.H. Sanders, R. K. Simidt, Statistics, A First Course, 1990
Other Sources	2. D.H. Sanders, R. K. Simidt, Statistics, A First Course, 1990

Evaluation System

Requirements	Number	Percentage of Grade
Attendance/Participation	-	-
Laboratory	-	-
Application	-	-
Field Work	-	-
Special Course Internship	-	-
Quizzes/Studio Critics	-	-
Homework Assignments	2	10
Presentation	-	-
Project	-	-
Report	-	-
Seminar	-	-
Midterms Exams/Midterms Jury	2	50
Final Exam/Final Jury	1	40
Toplam	5	100

Percentage of Semester Work	60
Percentage of Final Work	40
Total	100

Course Category

Core Courses
Major Area Courses
Supportive Courses	X
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

#	Program Qualifications / Competencies	Level of Contribution
#	Program Qualifications / Competencies	1	2	3	4	5
1	Acquiring the skills of understanding, explaining, and using the fundamental concepts and methods of economics
2	Acquiring the skills of macro level economic analysis
3	Acquiring the skills of micro level economic analysis
4	Understanding the formulation and implementation of economic policies at the local, national, regional, and/or global level
5	Learning different approaches on economic and related issues
6	Acquiring the quantitative and/or qualitative techniques in economic analysis
7	Improving the ability to use the modern software, hardware and/or technological devices
8	Developing intra-disciplinary and inter-disciplinary team work skills
9	Acquiring an open-minded behavior through encouraging critical analysis, discussions, and/or life-long learning
10	Adopting work ethic and social responsibility
11	Developing the skills of communication.
12	Improving the ability to effectively implement the knowledge and skills in at least one of the following areas: economic policy, public policy, international economic relations, industrial relations, monetary and financial affairs.

ECTS/Workload Table

Activities	Number	Duration (Hours)	Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class	14	3	42
Presentation/Seminar Prepration
Project
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury	2	10	20
Prepration of Final Exams/Final Jury	1	15	15
Total Workload			77