ECONOMICS AND FINANCE
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
ECO2063 Statistics for Economics Fall 3 0 3 6
The course opens with the approval of the Department at the beginning of each semester

Basic information

Language of instruction: En
Type of course: Must Course
Course Level: Bachelor
Mode of Delivery: Face to face
Course Coordinator : Assist. Prof. SERKAN YEŞİLYURT
Course Objectives: The objective of this course is to familiarize the students with the basic concepts of statistics and statistical computing with R software language to provide a solid foundation for further study and/or employment involving data analysis.

Learning Outputs

The students who have succeeded in this course;
• Explain the basic concepts, elements and objectives of inferential statistics
• Make inferential statistical analysis on a given data
• Use corresponding technology that inference procedures require actively learn and develop computer-based skills of inferential methods
• Apply inferential methods to enhance data-based decisions.
• Effectively communicate the results obtained from statistical analysis
• Make analytical inferences about and interpret publicly available information

Course Content

The teaching methods of the course are Lecture, Technology-Enhanced Learning,Problem Solving.
Students learn, within the scope of this course, the basic elements of inferential statistics such as theoretical framework of sampling distribution, confidence interval and hypothesis testing, along with R Studio applications.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction Reminder of R Concepts and Applied Statistics Getting Started with R Installing R Typing commands at R console Simple calculation with R Using basic functions
2) R Concepts and Applied Statistics Reminder of R Concepts and Applied Statistics Using commands Installing and loading related Packages for applied statistics Managing working directory Loading different extensions Data (csv, excel, rds)
3) Örnekleme ve Örnekleme Dağılımı Chapter 6 (Newbold & Carlson & Thorne)
4) Sampling and Sampling Distribution Chapter 6 (Newbold & Carlson & Thorne)
5) Confidence Interval Estimation: One Population Chapter 7 (Newbold & Carlson & Thorne)
6) Confidence Interval Estimation: One Population Chapter 7 (Newbold & Carlson & Thorne)
7) Confidence Interval Estimation: One Population Chapter 7 (Newbold & Carlson & Thorne)
8) Midterm Exam
9) Confidence Interval Estimation: Difference Between Normal Population Means Chapter 8 (Newbold & Carlson & Thorne)
10) Confidence Interval Estimation: Difference Between Normal Population Proportions Chapter 8 (Newbold & Carlson & Thorne)
11) Hypothesis Tests of a Single Population Chapter 9 (Newbold & Carlson & Thorne)
12) Hypothesis Tests of a Single Population Chapter 9 (Newbold & Carlson & Thorne)
13) Hypothesis Tests of a Two Population Chapter 10 (Newbold & Carlson & Thorne)
14) Hypothesis Tests of a Two Population Chapter 10 (Newbold & Carlson & Thorne)

Sources

Course Notes: The main textbook of the course: Newbold, P., Carlson, W.L., Thorne, B., (2024), (NCT abbreviation) Statistics For Business and Economics, 10th Global Edition. Learning platform: MyLab Statistics The ebook and the slides of the textbook through Pearson learning platform MyLab Statistics. Students will submit their three HWs over this platform.
References: D.R. Anderson, D.J. Sweeney and T.A. Williams, Freeman, J., Shoesmith, E. (2014), Statistics for Business and Economics, South-Western Cengage Learning. 3rd Edition. (2nd ed. can also be used.) For the students who would like to follow one textbook and the statistical terminology in Turkish: Şenesen, Ümit, İstatistik, Sayıların Arkasını Anlamak, Literatür Yayıncılık, (2013), İstanbul.

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Attendance 14 % 5
Laboratory % 0
Application % 0
Field Work % 0
Special Course Internship (Work Placement) % 0
Quizzes % 0
Homework Assignments 3 % 20
Presentation % 0
Project % 0
Seminar % 0
Midterms 1 % 35
Preliminary Jury % 0
Final 1 % 40
Paper Submission % 0
Jury % 0
Bütünleme % 0
Total % 100
PERCENTAGE OF SEMESTER WORK % 60
PERCENTAGE OF FINAL WORK % 40
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 13 3 39
Laboratory 0 0 0
Application 0 0 0
Special Course Internship (Work Placement) 0 0 0
Field Work 0 0 0
Study Hours Out of Class 14 7 98
Presentations / Seminar 0 0 0
Project 0 0 0
Homework Assignments 2 5 10
Quizzes 0 0 0
Preliminary Jury 0 0 0
Midterms 1 1 1
Paper Submission 0 0 0
Jury 0 0 0
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) Build up a body of knowledge in mathematics and statistics, to use them, to understand how the mechanism of economy –both at micro and macro levels – works. 5
2) Understand the common as well as distinctive characters of the markets, industries, market regulations and policies. 2
3) Developing the ability to explain global economic events by understanding different economic perspectives. 1
4) Acquiring the ability to analyze the impact of politics on the economy and vice versa. 1
5) Gaining the competence to propose solutions to economic problems and evaluate opposing policy recommendations. 3
6) Understanding and evaluating new economic developments and approaches. 4
7) Developing the ability to convey economic news and developments through written, oral, and graphical communication. 4
8) Gaining the competence to develop structured solutions for economic issues. 5
9) Acquiring the capability to present findings that support economic assumptions using numerical and verbal skills. 5
10) Gaining the competence to follow economic information and communicate with colleagues using a foreign language. 3