Faculty of Business and Management Sciences · International Trade and Finance · Undergraduate
ECTS: 5 T+P+L: 3+0+0 Compulsory
Coordinator: Dr. Öğr. Üyesi Safa YILDIRAN
Course Objective
This course focuses on statistical methods used in data analysis and decision-making. Topics include confidence intervals, hypothesis testing, comparisons of means and proportions, correlation and regression, chi-square tests, analysis of variance (ANOVA), nonparametric statistics, and sampling techniques. Emphasis is placed on practical applications in business, economics, and engineering.
Course Content
Expectations and Goals:
By the end of this course, students should be able to:
- Construct and interpret confidence intervals.
- Perform hypothesis testing and analyze differences between groups.
- Apply correlation and regression techniques to real-world data.
- Use chi-square tests and ANOVA for categorical and variance analysis.
- Implement nonparametric statistical methods when appropriate.
- Understand sampling techniques and their role in statistical inference.
Students are expected to actively participate, apply statistical tools using software, and develop analytical problem-solving skills.
Course Learning Outcomes
- Understands and applies nonparametric statistical methods for data analysis.
- Communicates statistical findings through tables, graphs, and technical reports.
- Recognizes and explains the principles of linear regression and correlation analysis.
- Understands and applies the concepts of multiple linear regression and certain nonlinear regression models.
- Analyzes data using one-factor experimental designs and general ANOVA techniques.
- Designs and evaluates factorial experiments involving two or more factors.
- Implements 2^𝑘 factorial experiments and fractional factorial designs for process optimization.
- Uses R or similar software for statistical analyses.
Core Area Distribution
(46) Mathematics and Statistics%60 (52) Engineering and Engineering Trades%40
Teaching Methods
ExpressionExercise and PracticeExperiment - Test / Lab/ Workshop / Field PracticeSelf studyProblem Solving
Assessment & Evaluation
HomeworkPerformance Assignment ( Lab / Workshop / Field Work / Seminar / Presentation / Completion Study / ThesisTesting (Essay / Tests: True-Falls, multiple-choice, short answer, matching)
ECTS / Workload
| Activity | Quantity | Duration (h) | Total Workload |
|---|---|---|---|
| Course Duration (Including Exam Week) | 16 | 3 | 48 |
| Out of Class Study Period | 16 | 2 | 32 |
| Midterm | 1 | 18 | 18 |
| Quiz | 2 | 4 | 8 |
| Assignment | 1 | 8 | 8 |
| Practice | 0 | 0 | 0 |
| Final | 1 | 22 | 22 |
Course Schedule
| Week | Subject | Preparation |
|---|---|---|
| 1 | Introduction to Course, Review of Statistics-I | - |
| 2 | Standard Normal Distribution - Z-distribution | |
| 3 | T-Distribution | - |
| 4 | Chi Square distribution | - |
| 5 | Confidence Intervals and sample size | - |
| 6 | Confidence Intervals and sample size | - |
| 7 | Mid-term examination | Mid-term examination |
| 8 | Hypothesis testing - t-distribution method | - |
| 9 | Hypothesis testing - Z-distribution method | - |
| 10 | Hypothesis testing - Chi square-distribution method | - |
| 11 | Simple Regression | - |
| 12 | Multiple Variable Regression Analysis | - |
| 13 | Multiple Variable Regression Analysis | - |
| 14 | Excel Application | - |
| 15 | FINAL EXAM and review | Study for Exam |
| 16 | RESIT EXAM and review | Study for Exam |