School/Faculty/Institute |
Faculty of Econ., Admin. and Social Sciences |
Course Code |
MATH 203 |
Course Title in English |
Probability and Statistics for Social Sciences I |
Course Title in Turkish |
Sosyal Bilimler için Olasılık ve İstatistik I |
Language of Instruction |
EN |
Type of Course |
Lecture |
Level of Course |
Introductory |
Semester |
Spring |
Contact Hours per Week |
Lecture: 3 |
Recitation: 0 |
Lab: 0 |
Other: 0 |
|
Estimated Student Workload |
150 hours per semester |
Number of Credits |
6 ECTS |
Grading Mode |
Standard Letter Grade
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Pre-requisites |
None |
Expected Prior Knowledge |
Knowledge of introductory level mathematical concepts |
Co-requisites |
None |
Registration Restrictions |
None |
Overall Educational Objective |
To learn the basic concepts of probability and statistics, recognize and distinguish the properties of important distributions and apply probability and statistics concepts in solving real life economic and business problems. |
Course Description |
This is first part of the year-round undergraduate course on probability and statistics for social sciences. Upon successful completion of the course, the participants are expected to be able to understand the idea of statistics and introduces useful methods for the collection, presentation, analysis, and interpretation of data. Some major topics are descriptive statistics, graphical description of data, measures of central tendency, dispersion and shape, probability, discrete and continuous random variables, discrete and continuous probability distributions. |
Course Description in Turkish |
Bu ders ekonomi ve işletme öğrencileri için hazırlanmış olan temel istatistik dersinin ilk kısmıdır. Ders başarı ile tamamlandığında, öğrenci, tanımlayıcı istatistikler, verinin grafiksel tanımı, merkezi eğilim, dağılım ve şekil ölçütleri, kesitli ve sürekli rassal değişkenler, kesitli ve sürekli olasılık dağılımları konularını öğrenmiş olmalı ve öğrencinin bu konularda yorum yapabilme becerisini geliştirmiş olması beklenmektedir. |
Course Learning Outcomes and Competences
Upon successful completion of the course, the learner is expected to be able to:
1) Solve real life probability problems using basic concepts of probability (counting, combinatorial methods, conditional probability, and Bayes’ theorem).
2) Recognize and distinguish the properties of important discrete probability distributions and solve real life problems using appropriate distributions. Explain the use of (and solve problems related with) expectation and variances.
3) Recognize and distinguish the properties of important continuous probability distributions and solve real life problems using appropriate distributions. Explain the use of (and solve problems related with) expectation and variance.
4) Understand the properties of joint probability distributions of multivariate random variables including marginal/conditional distribution/expectation.
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Program Learning Outcomes/Course Learning Outcomes |
1 |
2 |
3 |
4 |
1) Has a broad understanding of economics with a deep exposure to other social sciences and mathematics. |
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2) Demonstrates knowledge and skills in understanding the interactions of different areas of economics. |
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3) Displays a sound comprehension of microeconomic and macroeconomic theory.
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4) Applies economic concepts to solve complex problems and enhance decision-making capability. |
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5) Uses quantitative techniques to analyze different economic systems.
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6) Applies theoretical knowledge to analyze issues regarding Turkish and global economies. |
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7) Demonstrates proficiency in statistical tools and mainstream software programs to process and evaluate economic data. |
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8) Behaves according to scientific and ethical values at all stages of economic analysis: data collection, interpretation and dissemination of findings.
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9) Uses written and spoken English effectively (at least CEFR B2 level) to exchange scientific information. |
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10) Exhibits individual and professional ethical behavior and social responsibility. |
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11) Displays learning skills necessary for further study with a high degree of autonomy |
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Relation to Program Outcomes and Competences
N None |
S Supportive |
H Highly Related |
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Program Outcomes and Competences |
Level |
Assessed by |
1) |
Has a broad understanding of economics with a deep exposure to other social sciences and mathematics. |
H |
|
2) |
Demonstrates knowledge and skills in understanding the interactions of different areas of economics. |
S |
|
3) |
Displays a sound comprehension of microeconomic and macroeconomic theory.
|
N |
|
4) |
Applies economic concepts to solve complex problems and enhance decision-making capability. |
S |
|
5) |
Uses quantitative techniques to analyze different economic systems.
|
N |
|
6) |
Applies theoretical knowledge to analyze issues regarding Turkish and global economies. |
N |
|
7) |
Demonstrates proficiency in statistical tools and mainstream software programs to process and evaluate economic data. |
H |
|
8) |
Behaves according to scientific and ethical values at all stages of economic analysis: data collection, interpretation and dissemination of findings.
|
S |
|
9) |
Uses written and spoken English effectively (at least CEFR B2 level) to exchange scientific information. |
S |
|
10) |
Exhibits individual and professional ethical behavior and social responsibility. |
S |
|
11) |
Displays learning skills necessary for further study with a high degree of autonomy |
S |
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Prepared by and Date |
NAROD ERKOL , December 2023 |
Course Coordinator |
NAROD ERKOL |
Semester |
Spring |
Name of Instructor |
Asst. Prof. Dr. NAROD ERKOL |
Course Contents
Week |
Subject |
1) |
Syllabus, Introduction |
2) |
Using graphs to describe data |
3) |
Using graphs to describe data |
4) |
Using numerical measures to describe data |
5) |
Using numerical measures to describe data |
6) |
Probability methods |
7) |
Probability methods |
8) |
Midterm exam |
9) |
Discrete probability distributions |
10) |
Discrete probability distributions |
11) |
Discrete probability distributions |
12) |
Continuous probability distributions |
13) |
Continuous probability distributions |
14) |
Joint, marginal, conditional distributions |
15) |
Final examination period |
16) |
Final examination period |
Required/Recommended Readings | Newbold, P., Carlson, W.L., Thorne, B.M. (2013) Statistics for Business and Economics, ninth edition. Pearson.
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Teaching Methods | Active Learning
Flipped Learning |
Homework and Projects | Post-class assignments |
Laboratory Work | NA |
Computer Use | NA |
Other Activities | Scheduled and unscheduled quizzes |
Assessment Methods |
Assessment Tools |
Count |
Weight |
Attendance |
14 |
% 0 |
Quiz(zes) |
1 |
% 10 |
Homework Assignments |
1 |
% 25 |
Midterm(s) |
1 |
% 25 |
Final Examination |
1 |
% 40 |
TOTAL |
% 100 |
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Course Administration |
erkoln@mef.edu.tr
02123953670
Course Instructor: Asst. Prof. Narod Erkol (erkoln@mef.edu.tr)
Attendance/participation: Students are expected to prepare for the lecture via pre-class assignments, videos and reading materials. Students are responsible to follow the announcements, course materials available on Blackboard system.
Formal use of e-mails: Students are expected to use their @mef accounts for email traffic. The instructor is only responsible for the information sent/received through Blackboard system and emails using @mef account. The course instructor assumes that any information sent through email will be received in 24 hours, unless a system problem occurs.
Grading and evaluation: Evaluation will be based on the student learning outcomes. It is strongly recommended to complete all the work in a timely fashion. Late submissions will not be accepted.
Missing projects: No make up unless a legitimate proof of absence is presented.
Missing final exam: Faculty regulations.
Academic integrity: All students of MEF University are expected to be honest and comply with academic integrity. Students are expected to do their own work and neither give nor receive unauthorized assistance. Disciplinary action will be taken in case of suspicion.
Improper behavior, academic dishonesty and plagiarism: Law on Higher Education Article 54.
Important: If the learner cannot collect at least 30 points from the activities other than the final exam, they can not take the final exam and will get an FZ grade. |