Course Name Code Semester T+U Hours Credit ECTS
Computer Applications In Statistics ENM 421 7 3 + 0 3 5
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level Bachelor's Degree
Course Type Optional
Course Coordinator Dr.Öğr.Üyesi NEVRA AKBİLEK
Course Lecturers
Course Assistants Res.Assit. E.Elçin GÜNAY
Course Category
Course Objective Analyze data by statistical techniques and interpret the results of the study to assist managers.
Course Content
# Course Learning Outcomes Teaching Methods Assessment Methods
1 Student will be able to classify raw data Lecture, Question-Answer, Motivations to Show, Homework,
2 Student will be able to make the data ready to analyze Lecture, Drilland Practice, Motivations to Show, Homework,
3 Student will be able to run SPSS for analyzing the data Lecture, Drilland Practice, Motivations to Show, Testing, Homework,
4 Student will be able to decide on appropriate test procedure to analize data Discussion, Drilland Practice, Lecture, Testing, Homework,
5 Student will be able to structure engineering decision-making problems as hypothesis tests Lecture, Discussion, Drilland Practice, Testing, Homework,
6 Student will be able to test hypothesis Drilland Practice, Discussion, Lecture, Homework, Testing,
7 Student will be able to analize data by SPSS Lecture, Drilland Practice, Motivations to Show, Testing, Homework,
8 Student will be able to visualize data and analyze graphics Motivations to Show, Drilland Practice, Lecture, Homework, Testing,
9 Student will be able to construct the results of the statistical tests Lecture, Discussion, Drilland Practice, Testing, Homework, Project / Design,
10 Student will be able to report the results of the study Drilland Practice, Discussion, Lecture, Testing, Homework, Project / Design,
Week Course Topics Preliminary Preparation
1 Sampling Distribution
2 Hypothesis Tests
3 Nonparametric Tests
4 Nonparametric Tests
5 Chi-Square Independent Test
6 ANOVA
7 One way and Two way ANOVA
8 Regression and correlation Analysis
9 Assumptions of linear regression, simple linear regression models
10 Multiple regression models
11 Tests for regression
12 Cluster Analysis
13 Factor Analysis
14 Discriminant Analysis
Resources
Course Notes
Course Resources
Order Program Outcomes Level of Contribution
1 2 3 4 5
1 Engineering graduates with sufficient knowledge background on science and engineering subjects of their related area, and who are skillful in implementing theoretical and practical knowledge for modelling and solving engineering problems. X
2 Engineering graduates with skills in identifying, describing, formulating and solving complex engineering problems, and thus,deciding and implementing appropriate methods for analyzing and modelling. X
3 Engineering graduates with skills in designing a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; for this purpose, skills in implementing modern design methods.
4 Engineering graduates with skills in developing, selecting and implementing modern techniques and tools required for engineering applications as well as with skills in using information technologies effectively. X
5 Engineering graduates with skills in designing and conducting experiments, collecting data, analyzing and interpreting the results in order to evaluate engineering problems. X
6 Engineering graduates who are able to work within a one discipline or multi-discipline team,as well as who are able to work individually X
7 Engineering graduates who are able to effectively communicate orally and officially in Turkish Language as well as who knows at least one foreign language X
8 Engineering graduates with motivation to life-long learning and having known significance of continuous education beyond undergraduate studies for science and technology X
9 Engineering graduates with well-structured responsibilities in profession and ethics X
10 Engineering graduates having knowledge about practices in professional life such as project management, risk management and change management, and who are aware of innovation and sustainable development. X
11 Engineering graduates having knowledge about universal and social effects of engineering applications on health, environment and safety, as well as having awareness for juridical consequences of engineering solutions.
Evaluation System
Semester Studies Contribution Rate
1. Ödev 60
1. Kısa Sınav 10
2. Ödev 30
Total 100
1. Yıl İçinin Başarıya 50
1. Final 50
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 1 16
Mid-terms 1 10 10
Quiz 2 6 12
Assignment 2 9 18
Final examination 1 10 10
Total Workload 114
Total Workload / 25 (Hours) 4.56
dersAKTSKredisi 5