STAT444 ADVANCED STATISTICAL COMPUTING
| Course Code: | 2460444 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 8.0 |
| Department: | Statistics |
| Language of Instruction: | English |
| Level of Study: | Undergraduate |
| Course Coordinator: | Prof.Dr. CEYLAN YOZGATLIGİL |
| Offered Semester: | Spring Semesters. |
Course Objectives
This course will help students to have the right skills to understand the basics of relational databases, learn structured query language (SQL) to an intermediate level, write SQL code to build and maintain database structures, update database content with SQL and transaction handling, retrieve data from single or multiple tables, process data with row and aggregate functions, manipulate data with correlated and noncorrelated subqueries.
Starting with database theory and planning, this course will explain how to create tables and populate them with data, managing forms, creating reports and importing data from other sources. Integration with SQL, MS Access database will be created. By creating sample database each step would be explained in lectures. So that after the course there would be a final database with each elements; tables, forms, queries and reports.
Course Content
This course focuses on the following key areas: reading raw data files and Statistical Analysis Software (SAS) data sets, and writing the results to SAS data sets; subsetting data; combining multiple SAS files; creating SAS variables and recording data values; creating listing and summary reports.
Course Learning Outcomes
Upon successful completion of the course, a student will be able to:
-Understand Database concept and its utilities.
-Uses of Structure Query Language(SQL) commands.
-Perform Query operation and Normalization of database.
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