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	Prof. Dr. Ayla OĞUŞ BİNATLI
Course Lecturer(s)	Dr.Öğretim Üyesi AYŞE ELİF AY YALÇINKAYA Öğr.Gör.Dr. ESEN ERDOĞAN ÇİFTÇİ Prof. Dr. Ayla OĞUŞ BİNATLI
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 categorical and numerical data to visualize business trends Analyze measures of central tendency and variation to interpret data distributions Solve probability problems using fundamental principles Apply discrete and continuous probability distributions to model business scenarios Calculate confidence intervals for single and double samples with normal distribution Use confidence intervals for business predictions and decisions Conduct hypothesis tests for normally distributed populations Explain the importance of probability in business contexts and evaluate data-driven decision making
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	Newbold, Carlson & Thorne Chapter 1 Cetinkaya-Rundel, M., Diez, D., & Barr, C. (2019). OpenIntro Statistics. Chapter 1
2	Summarizing data: Examining numerical data and categorical data	Newbold, Carlson & Thorne Chapter 2 OpenIntro Statistics. Chapter 2
3	Probability: Defining Probability	Newbold, Carlson & Thorne Chapter 3.1-3.2 OpenIntro Statistics. Chapter 3.1
4	Probability: Conditional Probability, Bivariate Probabilities and The Bayes Theorem	Newbold, Carlson & Thorne Chapter 3.3-3.5 OpenIntro Statistics. Chapter 3.2
5	Probability: Sampling, Random Variables, Discrete Distributions, Continuous Distributions	Newbold, Carlson & Thorne Chapters 4.1-4.3, 5.1-5.2 OpenIntro Statistics. Chapter 3.3 & 3.4 & 3.5
6	Distributions of Random Variables: Continuous Distributions, Uniform Distribution, Normal Distribution	Newbold, Carlson & Thorne Chapters 5.1- 5.3 OpenIntro Statistics. Chapters 4.1
7	Distributions of Random Variables: Normal Dist. Cont’d., Discrete Distributions: Binomial Distribution	Newbold, Carlson & Thorne Chapters 4.4, 4.6, 5.4 OpenIntro Statistics. Chapters 4.1, 4.3
8	Distributions of discrete RVs: Poisson distribution and review before exam	Newbold, Carlson & Thorne Chapter 4.5 OpenIntro Statistics. Chapter 5.1
9	Midterm Exam	Midterm Exam
10	Foundations for Inference: Point Estimates and Sampling Variability	Newbold, Carlson & Thorne Chapter 6 OpenIntro Statistics. Chapter 5.2
11	Foundations for Inference: Confidence Intervals for a Proportion and for a Population Mean	Newbold, Carlson & Thorne Chapters 7.2, 7.4, 7.7-7.8 OpenIntro Statistics. Chapter 5.3
12	Foundations for Inference: Hypothesis Testing: Single Population Proportion, Single Population Mean with known Variance, Decision Errors, P-value, Statistical Significance	Newbold, Carlson & Thorne Chapters 9.1, 9.2, 9.4 OpenIntro Statistics. Chapter 6.1 & 6.2
13	Hypothesis Testing and Inference: The Chi-square Distribution, Tests of Variance, Testing for goodness of fit using chi-square; Chi-Square test of Independence	Newbold, Carlson & Thorne Chapter 9.6 OpenIntro Statistics. Chapter 6.3 & 6.4
14	Hypothesis Testing and Inference: The Student’s t-Distribution, Single Population Mean with unknown variance	Newbold, Carlson & Thorne Chapter 9.3 OpenIntro Statistics. Chapter 7.1.1-7.1.3
15	Hypothesis Testing, CI and Inference: Difference between two population means with known or unknown variance, Difference between two proportions	Newbold, Carlson & Thorne Chapters 10.3, 8.1, 8.3 OpenIntro Statistics. Chapter 7.1.4, 7.1.5 & 7.2
16	Final Exam	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	-	X	-	-	-
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	-	-	-	-	X
7	To be able to design, plan and model in order to contribute to decision making within the scope of logistics and supply chains	-	-	-	X	-
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.	-	-	-	-	-