ECON 280 | Course Introduction and Application Information - Department of Logistics Management

Course Name

Statistics for Business & Economics

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
ECON 280	Fall	2	2	3	6

Prerequisites	None
Course Language	English
Course Type	Required
Course Level	First Cycle
Mode of Delivery	-
Teaching Methods and Techniques of the Course	Problem Solving Application: Experiment / Laboratory / Workshop Lecture / Presentation
National Occupation Classification	-
Course Coordinator	Doç. Dr. Gül ERTAN ÖZGÜZER
Course Lecturer(s)	Doç. Dr. Gül ERTAN ÖZGÜZER Dr. Öğr. Üyesi EZGİ ÖZSÖĞÜT Öğr. Gör. Dr. Esen ERDOĞAN ÇİFTÇİ
Assistant(s)	Araş. Gör. Hasan GÜLOĞLU

Course Objectives	This course aims to provide students in business and economics fields with a solid foundation in probability and statistics, teaching them the necessary statistical methods and tools for data analysis and interpretation, and enabling their effective application in real-world business and economic contexts. Thus, students will be able to understand probability and statistics theoretically and also use them in practice to solve business and economic problems.
Learning Outcomes	The students who succeeded in this course; Create and interpret graphs for both categorical and numerical data to visualize business and economic trends and insights. Analyze measures of central tendency and variation to understand data distributions and make informed business and economic decisions. Solve a variety of probability problems using fundamental principles, enhancing their decision-making under uncertainty. Apply specific discrete and continuous probability distributions to model and analyze business scenarios. Calculate confidence intervals for single and double samples with normal distribution, regardless of whether the population variance is known or unknown, to estimate business metrics accurately. Employ confidence intervals in making predictions and decisions in business contexts. Conduct hypothesis tests for one or two populations with normal distributions to validate business assumptions and strategies. Recognize the importance of probability and statistics in addressing real-world business and economic challenges, fostering a data-driven approach to problem-solving.
Course Description	This course, designed for business faculty students, dives into probability essentials, covering discrete and continuous distributions and sampling distribution creation. It sharpens skills in estimating confidence intervals and in conducting hypothesis testing for single and dual population scenarios. Bridging theory with practical business and economic applications, the course prepares students to apply statistical tools in decision-making and strategic analysis, readying them to face real-world business challenges confidently.
Related Sustainable Development Goals

Course Category	Core Courses
	Major Area Courses
	Supportive Courses
	Media and Management Skills Courses
	Transferable Skill Courses

Week	Subjects	Related Preparation
1	Introduction to Data: Intro, Case Study; Data Basics, Sampling Principles and Strategies Experiments	Cetinkaya-Rundel, M., Diez, D., & Barr, C. (2019). OpenIntro Statistics. Chapter 1
2	Summarizing data: Examining numerical data and categorical data	OpenIntro Statistics. Chapter 2
3	Probability: Defining Probability	OpenIntro Statistics. Chapter 3.1
4	Probability: Conditional Probability	OpenIntro Statistics. Chapter 3.2
5	Probability: Sampling, Random Variables, Continuous Distributions	OpenIntro Statistics. Chapter 3.3 & 3.4 & 3.5
6	Distributions of Random Variables: Normal Distribution	OpenIntro Statistics. Chapters 4.1
7	Distributions of Random Variables: Binomial Distribution, Poisson Distribution	OpenIntro Statistics. Chapter 4.3 & 4.5
8	Mid-term Exam I	Midterm exams week- No class
9	Foundations for Inference: Point Estimates and Sampling Variability	OpenIntro Statistics. Chapter 5.1
10	Foundations for Inference: Confidence Intervals for a Proportion	OpenIntro Statistics. Chapter 5.2
11	Foundations for Inference: Hypothesis Testing: Single Population Proportion, Decision Errors, P-value, Statistical Significance	OpenIntro Statistics. Chapter 5.3
12	Inference for categorical data: Inference for Single Proportion; Difference of Two Proportions	OpenIntro Statistics. Chapter 6.1 & 6.2
13	Inference for categorical data: Testing for goodness of fit using chi-square; Chi-Square test of Independence	OpenIntro Statistics. Chapter 6.3 & 6.4
14	Inference for numerical data: One-sample means with the t-distribution	OpenIntro Statistics. Chapter 7.1.1-7.1.3
15	Inference for numerical data: One sample t-confidence intervals, t-tests & Paired data	OpenIntro Statistics. Chapter 7.1.4, 7.1.5 & 7.2
16	Final Exam

Course Notes/Textbooks

Cetinkaya-Rundel, M., Diez, D., & Barr, C. (2019). OpenIntro Statistics. (Fourth Edition ed.) OpenIntro, Inc. https://www.openintro.org/book/os/

Newbold P., Carlson W.L., Thorne B., Statistics for Business and Economics, 10th edition (Pearson

Suggested Readings/Materials

Lind D., Marchal S., Statistical Techniques in Business & Economics, 17th edition (McGraw-Hill, 2017), ISBN-13: 978-1259666360

Semester Activities	Number	Weigthing
Participation	1	5
Laboratory / Application	1	10
Field Work
Quizzes / Studio Critiques	1	20
Portfolio
Homework / Assignments
Presentation / Jury
Project	1	15
Seminar / Workshop
Oral Exams
Midterm	1	25
Final Exam	1	25
Total

Weighting of Semester Activities on the Final Grade	5	70
Weighting of End-of-Semester Activities on the Final Grade	1	30
Total

Semester Activities	Number	Duration (Hours)	Workload
Theoretical Course Hours (Including exam week: 16 x total hours)	16	2	32
Laboratory / Application Hours (Including exam week: '.16.' x total hours)	16	2	32
Study Hours Out of Class	16	1.5	24
Field Work			0
Quizzes / Studio Critiques	1	12	12
Portfolio			0
Homework / Assignments			0
Presentation / Jury			0
Project	1	24	24
Seminar / Workshop			0
Oral Exam			0
Midterms	1	24	24
Final Exam	1	32	32
		Total	180

#	Program Competencies/Outcomes	* Contribution Level
#	Program Competencies/Outcomes	1	2	3	4	5
1	To be able to analyze complex problems in the field of logistics and supply chains	-	-	-	-	-
2	To be able to have good knowledge of sector related market leaders, professional organizations, and contemporary developments in the logistics sector and supply chains	-	-	-	-	-
3	To be able to participate in the sector-related communication networks and improve professional competencies within the business sector	-	-	-	-	-
4	To be able to use necessary software, information and communication technologies in the fields of logistics management and supply chain	-	-	-	-	-
5	To be able to understand and utilize the coordination mechanisms and supply chain integration	-	-	-	-	-
6	To be able to analyze the logistics and supply chain processes using the management science perspective and analytical approaches	-	-	-	-	-
7	To be able to design, plan and model in order to contribute to decision making within the scope of logistics and supply chains	-	-	-	-	-
8	To be able to interpret and evaluate the classical and contemporary theories in the field of logistics and supply chains	-	-	-	-	-
9	To be able to conduct projects and participate in teamwork in the field of logistics and supply chains	-	-	-	-	-
10	To be able to have an ethical perspective and social responsiveness when making and evaluating decisions.	-	-	-	-	-
11	To be able to collect data in the area of logistics and communicate with colleagues in a foreign language ("European Language Portfolio Global Scale", Level B1).	-	-	-	-	-
12	To be able to speak a second foreign at a medium level of fluency efficiently.	-	-	-	-	-
13	To be able to relate the knowledge accumulated throughout human history to their field of expertise.	-	-	-	-	-