BUSINESS ADMINISTRATION
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
ECO2061	Statistics	Spring	3	0	3	6

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Assist. Prof. EMİNE ZEREN TAŞPINAR
Course Lecturer(s):	Assoc. Prof. DEREN ÜNALMIŞ Assist. Prof. EMİNE ZEREN TAŞPINAR Assist. Prof. BAHAR KÖSEOĞLU Assist. Prof. AYSE ERTUĞRUL BAYKAN
Recommended Optional Program Components:	None
Course Objectives:	Statistics is about reading, interpreting, and playing with data that you frequently encounter in your daily life and/or professional life. This course aims to make you familiar with basic statistical tools which are necessary to deal with data.

Learning Outcomes

The students who have succeeded in this course;
• classify, read, and interpret data.
• calculate and visualize descriptive statistics using Excel and interpret these summary measures.
• understand the basics of probability.
• define random variables and the basics of the probability distribution of these random variables.
• use tools in Excel related to probability and probability distribution functions.

Course Content

Introduction and Data Collection
Presenting Data in Tables And Charts (Organizing Categorical Data)
Presenting Data in Tables And Charts (Frequency Distribution)
Presenting Data in Tables And Charts (Organizing Numerical Data)
Numerical Descriptive Measures (Measures of Central Tendency)
Numerical Descriptive Measures (Measures of Variation)
Numerical Descriptive Measures (Z-Score and Shape of a Distribution)
Basic Probability (Basic Probability Concepts)
Basic Probability (Basic Probability Concepts, Simple and Joint Probabilities)
Basic Probability (Conditional Probabilities)
Discrete Probability Distributions (Basic Concepts and Expected Value)
Discrete Probability Distributions (Binomial and Poisson Distributions)
Continuous Distributions (Normal Distribution)
Continuous Distributions (Uniform Distributions and Exponential Distribuitons)

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction
2)	Using Graphs to Describe Data	Basic concepts of statistics, using graphs and tables to describe data. • Types of variables and levels of measurement • Sources of data • Organizing and describing categorical data • Organizing and describing numerical data • Visualizing two numerical variables: Time series plot
3)	Using Numerical Measures to Describe Data	• Measure of Central Tendency • Measure of variation • Measure of shape • Locating Extreme outliers: Z-score
4)	Using Numerical Measures to Describe Data	Empirical rule Chebyshev rule Covariance
5)	Elements Of Chance: Probability Methods	Concepts and definitions Approaches in assessing probability 1. Classical probability: Permutations, Combinations 2. Relative frequency probability
6)	Elements Of Chance: Probability Methods	Probability rules Probability table (Two-way/Joint Probability table) Conditional probability Tree diagram and Venn diagram
7)	Elements Of Chance: Probability Methods	Bayes’ Theorem
8)	Midterm Exam
9)	Discrete Probability Distributions	Random Variables (RV) Probability Distribution Function Summary Measures of a Discrete RV Functions of Discrete RV
10)	Discrete Probability Distributions	Binomial Distr., Poisson Distr., Hypergeometric Distr.
11)	Continuous Probability Distributions	Continuous RV CDF, PDF Probability as an Area Expectations and Linear Functions of Continuous RV
12)	Continuous Probability Distributions	Uniform Distr., Normal & Standard Normal Distr.
13)	Continuous Probability Distributions	Exponential Distr.
14)	Joint Distributions Review	Jointly Distributed Discrete and Continuous RV

Sources

Course Notes / Textbooks:	Statistics for Business and Economics, Paul Newbold, William L. Carlson and Betty Thorne, 9th Edition, Pearson. (NCT)
References:

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Midterms	1	% 40
Final	1	% 60
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	7	98
Quizzes	3	2	6
Midterms	1	2	2
Final	1	2	2
Total Workload			150

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Being able to identify problems and ask right questions	5
2)	Having problem solving skills and developing necessary analytical attitude	5
3)	Comprehending theoretical arguments along with counter arguments in detail	1
4)	Gaining awareness of lifelong learning and being qualified for pursuing graduate education	5
5)	Applying theoretical concepts in project planning	2
6)	Communicating efficiently by accepting differences and carrying out compatible teamwork
7)	Increasing efficiency rate in business environment	4
8)	Developing innovative and creative solutions in face of uncertainty	3
9)	Researching to gather information for understanding current threats and opportunities in business	5
10)	Being aware of the effects of globalization on society and business while deciding
11)	Possessing digital competence and utilizing necessary technology	5
12)	Communicating in at least one foreign language in academic and daily life	3
13)	Possessing managing skills and competence	3
14)	Deciding with the awareness of the legal and ethical consequences of business operations	3
15)	Expressing opinions that are built through critical thinking process in business and academic environment	4