| Course Type | Compulsory Course |
|---|
| Course Level | Bachelor's Degree |
|---|
| Year of Study | 2 |
|---|
| Semester | Fourth Term (Spring) |
|---|
| ECTS | 4 |
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| Name of Lecturer(s) |
|
| Learning Outcomes |
At the end of this course, the students;
- Explain the fundamental properties of binomial, Poisson, and normal distributions and their areas of application.
- Describe convergence properties between different distributions and illustrate these properties with relevant examples.
- Define the basic characteristics of sample and population distributions, analyzing the relationships between them.
- Calculate point and interval estimates for data and interpret the meaning of these estimates.
- Create confidence intervals by analyzing sample data and draw conclusions about population parameters based on these intervals.
- Formulate hypothesis tests for single population parameters (mean, variance, proportion), select appropriate tests, apply them, and evaluate the results.
- Formulate hypothesis tests for two population parameters (mean, variance, proportion), select appropriate tests, apply them, and interpret the results.
- Calculate the correlation coefficient between data sets, conduct simple linear regression analysis, and interpret the results.
- Use the SPSS program effectively in statistical analyses, manage the analysis processes, and evaluate the results.
|
| Mode of Delivery | Face to face |
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| Prerequisites | Yes(TBF221) |
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| Recommended Optional Programme Components | None |
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| Course Description | This course aims to develop statistical analysis skills such as sample distributions, confidence intervals, hypothesis testing, and linear regression analysis. |
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| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Review of binomial, Poisson, and normal distributions |
|
2nd Week |
Convergence of binomial and Poisson distributions to normal distribution |
|
3rd Week |
Distributions of sample means |
|
4th Week |
Distributions of sample proportions and variances |
|
5th Week |
Point and interval estimates, confidence intervals for population means |
|
6th Week |
Confidence intervals for population proportions and variances |
|
7th Week |
Problem solving |
|
8th Week |
Midterm exam |
|
9th Week |
Hypothesis tests for single population means |
|
10th Week |
Hypothesis tests for single population variances and proportions |
|
11th Week |
Hypothesis tests and confidence intervals for two population means |
|
12th Week |
Hypothesis tests and confidence intervals for two population variances and proportions |
|
13th Week |
Correlation coefficient, linear regression analysis |
|
14th Week |
General review |
|
| Recommended or Required Reading | Groebner, D. F., Shannon, P. W., Fry, P. C., & Smith, K. D. (2023). Business statistics: A decision-making approach (11th ed.). Pearson.
Cula, S., & Muluk, F. Z. (2010). Temel istatistik yöntemleri (2nd ed.). Başkent Üniversitesi. |
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| Planned Learning Activities and Teaching Methods |
- Lecture
- Questions/Answers
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
30 |
| Quiz |
3 |
10 |
| Project |
1 |
15 |
| Total(%) |
|
55 |
| Contribution of In-term Studies to Overall Grade(%) |
|
55 |
| Contribution of Final Examination to Overall Grade(%) |
|
45 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
1 |
1 |
| Preparation for Quiz |
3 |
5 |
15 |
| Individual or group work |
14 |
1 |
14 |
| Preparation for Final exam |
1 |
30 |
30 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
15 |
15 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
1 |
1 |
| Homework |
|
|
|
| Project |
1 |
10 |
10 |
| Total Work Load | 128 |
| Total Work Load / 30 (h) | 4.26 |
| ECTS Credit of the Course | 4 |
|
| Language of Instruction | Turkish |
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| Work Placement(s) | No |
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