| Course Unit Code | Course Unit Title | Type of Course Unit | Year of Study | Semester | Number of ECTS Credits | | İKT206B2 | Statistics II | Compulsory | 2 | 4 | 4 |
|
| Level of Course Unit |
| First Cycle |
| Objectives of the Course |
| Statistics 2 course aims to provide students with more advanced applications of statistical methods and data analysis skills. This course makes students more competent and equipped in the field of statistics and further reinforces their statistical problem solving skills. |
| Name of Lecturer(s) |
| Doç. Dr. Hakan Pabuçcu |
| Learning Outcomes |
| 1 | The student should be able to estimate confidence intervals for a population parameter.
The student should be able to select and apply appropriate statistical tests to test a given hypothesis.
The student should be able to draw statistically significant conclusions by interpreting the results of hypothesis testing. | | 2 | The student should have the ability to perform regression analysis to analyse the relationship between two or more variables. | | 3 | The student should have the ability to use analysis of variance techniques to determine the differences between groups. | | 4 | The learner should be able to analyse the reasons for differences between groups based on ANOVA results. | | 5 | helps students to improve their ability to solve statistical problems and interpret data correctly. |
|
| Mode of Delivery |
| Normal Education |
| Prerequisites and co-requisities |
| None |
| Recommended Optional Programme Components |
| None |
| Course Contents |
| Confidence Intervals and Hypothesis Tests: The student should be able to calculate confidence intervals, perform hypothesis testing and interpret the results.
Regression and Correlation Analysis: The student should be able to perform regression and correlation analysis and interpret the relationship between variables.
Analysis of Variance (ANOVA): A more in-depth study of ANOVA techniques and the application of different analysis of variance models. |
| Weekly Detailed Course Contents |
|
| 1 | What is a confidence interval?
Confidence interval calculation methods | | | | 2 | Confidence intervals for ratios
Confidence intervals for averages | | | | 3 | Practical examples about confidence intervals | | | | 4 | What is hypothesis testing?
One sample hypothesis tests
Two sample hypothesis tests | | | | 5 | ANOVA (Analysis of Variance) basics
Hypothesis testing applications | | | | 6 | What is the correlation coefficient?
Pearson correlation coefficient
Spearman correlation coefficient | | | | 7 | Mid term exam | | | | 8 | Interpretation of the correlation
Correlation analysis applications | | | | 9 | What is regression analysis? Simple linear regression | | | | 10 | Multiple linear regression
Assumptions in regression analysis
Regression analysis applications | | | | 11 | What is analysis of variance?
One-way ANOVA
Two-way ANOVA | | | | 12 | Interpretation of variance analysis results
Analysis of variance applications | | | | 13 | Probability distributions | | | | 14 | Probability distributions | | |
|
| Recommended or Required Reading |
| Akdeniz, F. (2022). Olasılık ve istatistik. Akademisyen Kitabevi. |
| Planned Learning Activities and Teaching Methods |
|
| Assessment Methods and Criteria | |
| Midterm Examination | 1 | 100 | | SUM | 100 | |
| Final Examination | 1 | 100 | | SUM | 100 | | Term (or Year) Learning Activities | 40 | | End Of Term (or Year) Learning Activities | 60 | | SUM | 100 |
| | Language of Instruction | | Turkish | | Work Placement(s) | | None |
|
| Workload Calculation |
|
| Midterm Examination | 1 | 50 | 50 |
| Final Examination | 1 | 80 | 80 |
|
| Contribution of Learning Outcomes to Programme Outcomes |
|
| * Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High |
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