STAT292 STATISTICAL COMPUTING II
| Course Code: | 2460292 |
| METU Credit (Theoretical-Laboratory hours/week): | 4 (3.00 - 2.00) |
| ECTS Credit: | 8.0 |
| Department: | Statistics |
| Language of Instruction: | English |
| Level of Study: | Undergraduate |
| Course Coordinator: | Prof.Dr. ZEYNEP IŞIL KALAYLIOĞLU AKYILDIZ |
| Offered Semester: | Spring Semesters. |
Course Objectives
We will attempt to cover some or all of the following data analysis technologies:
- R
- R-Shiny
- Data visualization
- UNIX
Course Content
Introduction to programming and computation. Introduction to computer organization and basic data structures. An advanced programming language with applications to statistical procedures.
Prerequisite: CENG 230
Course Learning Outcomes
Computational tools for representing, manipulating, interpreting, transforming, and visualizing data. Covering statistical topics such as random number generation, probability distributions and linear models in R. Creating reproducible analysis and research reports in R. Automation for repeatable analysis. Focus on in-memory data to be able to handle with big data. Some prior computational or statistical experience is necessary.
Program Outcomes Matrix
| Level of Contribution | |||||
| # | Program Outcomes | 0 | 1 | 2 | 3 |
| 1 | Applying the knowledge of statistics, mathematics and computer to statistical problems and developing analytical solutions. | ✔ | |||
| 2 | Defining, modeling and solving real life problems that involve uncertainty, and interpreting results. | ✔ | |||
| 3 | To decide on the data collection technique, and apply it through experiment, observation, questionnaire or simulation. | ✔ | |||
| 4 | Analysing small and big volumes of data and interpreting results. | ✔ | |||
| 5 | Utilizing up-to-date techniques, computer hardware and software required for statistical applications; developing software programs and numerical solutions for specific problems when necessary. | ✔ | |||
| 6 | Taking part in intradisciplinary and interdisciplinary teamwork, using time efficiently, taking leadership responsibilities and being entrepreneurial. | ✔ | |||
| 7 | Taking responsibility in individual work and offering authentic solutions. | ✔ | |||
| 8 | Following contemporary developments and publications in statistical science, conducting research, being open to novelty and thinking critically. | ✔ | |||
| 9 | Efficiently communicating in Turkish and English to define and analyze statistical problems and to interpret the results. | ✔ | |||
| 10 | Having a professional and ethical sense of responsibility. | ✔ | |||
| 11 | Developing computational solutions to statistical problems that cannot be solved analytically. | ✔ | |||
| 12 | Having theoretical background and developing new theories in statistics, building relations between theoretical and practical knowledge. | ✔ | |||
| 13 | Serving the society with the expertise in the field. | ✔ | |||
0: No Contribution 1: Little Contribution 2: Partial Contribution 3: Full Contribution