COURSE INTRODUCTION AND APPLICATION INFORMATION


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
Course Coordinator
Course Lecturer(s)
Assistant(s)
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
X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Required Materials
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

 

EVALUATION SYSTEM

Semester Activities Number Weighting
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 Exam
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

ECTS / WORKLOAD TABLE

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

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To be able to acquire a sound knowledge of fundamental concepts, theories, principles and methods of investigation specific to the economic field.

X
2

To be able to apply adequate mathematical, econometric, statistical and data analysis models to process economic data and to implement scientific research for development of economic policies.

X
3

To be able to participate in academic, professional, regional, and global networks and to utilize these networks efficiently.

4

To be able to have adequate social responsibility with regards to the needs of the society and to organize the activities to influence social dynamics in line with social goals.

5

To be able to integrate the knowledge and training acquired during the university education with personal education and produce a synthesis of knowledge one requires.

6

To be able to evaluate his/her advance level educational needs and do necessary planning to fulfill those needs through the acquired capability to think analytically and critically.

X
7

To be able to acquire necessary skills to integrate social dynamics into economic process both as an input and an output.

X
8

To be able to link accumulated knowledge acquired during the university education with historical and cultural qualities of the society and be able to convey it to different strata of society.

9

To be able to take the responsibility as an individual and as a team member.

10

To be able to attain social, scientific and ethical values at the data collection, interpretation and dissemination stages of economic analysis.

X
11

To be able to collect data in economics and communicate with colleagues in a foreign language ("European Language Portfolio Global Scale", Level B1)

12

To be able to speak a second foreign language at a medium level of fluency efficiently.

13

To be able to relate the knowledge accumulated throughout human history to their field of economics.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest