| Course Type | Elective Course |
|---|
| Course Level | Bachelor's Degree |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 5 |
|---|
| Name of Lecturer(s) |
|
| Learning Outcomes |
At the end of this course, the students;
- Know a wide range of data analytics techniques (descriptive analytics, inferential analytics, and predictive analytics).
- Master different data analysis problems encountered in applications with heavy data use.
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | Data Science |
|---|
| Course Description | Data Analytics is the science of analyzing data to convert information to useful knowledge. This knowledge could help us to make better decisions. This course aims to present you with a wide range of data analytic techniques (descriptive, inferential, predictive, and prescriptive analytics). |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Basic Definitions: Data, Data Analytics, Parametric and Non-parametric tests |
|
2nd Week |
Testing Assumptions for Parametric Tests |
|
3rd Week |
One Sample T Test and Wilcoxon Signed Rank Test |
|
4th Week |
Independent Samples T Test and Mann-Whitney U Test |
|
5th Week |
Paired Samples T Test and Wİlcoxon Signed Rank Test |
|
6th Week |
One Way ANOVA and Kruskal Wallis' H Test |
|
7th Week |
Repetition |
|
8th Week |
Mid-term Examination |
|
9th Week |
Two Ways ANOVA and Friedman's S Test |
|
10th Week |
Chi-Square Tests for Independence, Goodness of Fit Tests |
|
11th Week |
Social Network Analysis |
|
12th Week |
Word Cloud |
|
13th Week |
Repetition |
|
14th Week |
Project Presentations |
|
| Recommended or Required Reading | "Univariate, Bivariate, and Multivariate Statistics Using R", Daniel J. Denis, Wiley, 2020.
"İstatistikte R ile Programlama", Necmi Gürsakal, Dora, 2018. |
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Discussion
- Problem Solving
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
30 |
| Project |
1 |
30 |
| Total(%) |
|
60 |
| Contribution of In-term Studies to Overall Grade(%) |
|
60 |
| Contribution of Final Examination to Overall Grade(%) |
|
40 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
2.5 |
2.5 |
| Preparation for Quiz |
|
|
|
| Individual or group work |
14 |
4 |
56 |
| Preparation for Final exam |
1 |
20 |
20 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
20 |
20 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
2.5 |
2.5 |
| Homework |
|
|
|
| Project |
1 |
6 |
6 |
| Total Work Load | 149 |
| Total Work Load / 30 (h) | 4.96 |
| ECTS Credit of the Course | 5 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
