MCM2206

UNDERGRADUATE COURSE DETAILS
Course Title: Statistics for Engineers
Code : MÇM2206
Education and Teaching Methods
Application
Laboratuary
Project/
Hw.
Field
Study
36
14
Lecture
42
4
Semester
Faculty or VS: E.A.F
Programme: Environmental
Engineering
Credits
Other
Total
Credit
T+A+L=Credit
ECTS
28
120
3+0+0=3
4
Turkish
Language
Course Type
Basic
Scientific
Course
Objectives
Learning
Outcomes
and
Competences
Aim of the course is to teach statistical methods and techniques in the process of data analysis by
using of computer-aided teaching.
Technical
Elective
Scientific
Social
Elective
At the end of this course, students will gain the ability to prepare data research topics relating to
specified data collection, classification and analysis of collected. Students will be able to make
appropriate statistical analysis purposed of the research.
1.
2.
3.
Textbook
and /or
References
Moore DS., 2003. The Basic Proctice of Statistics, Third Edition,
Ural A., Kılıç İ., 2005, Bilimsel Araştırma Süreci ve SPSS ile Veri Analizi, Detay Yayıncılık.
Gerber SB., Finn KV., 2005. Using SPSS for Windows, Data analysis and Graphics,
Springer.
ASSESSMENT CRITERIA
Theoretical Courses
Midterm Exams
Project Course and Graduation Study
If any,
mark as
(X)
Percent
(%)
X
20
If any,
mark as
(X)
Percent
(%)
Midterm Exams
Midterm
Controls
Quizzes
Homeworks
X
10
Term Paper
Term Paper, Project
Reports, etc.
X
10
Oral
Examination
Laboratory Work
Final Exam
Final Exam
X
60
Other
Other
Week
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Subjects
Scientific research process
The definition of statistics and functions: data acquisition, analysis of the distribution,
presentation techniques
Universe and Sample: universe definition, sampling methods, sampling errors
The selection of statistical methods to be used for data analysis
Basic statistics: descriptive statistics, frequency analysis
Variable definitions, distribution models, graphical impressions
Data, variables, distributions, graphical distribution, descriptive statistics related to computer
applications
Midterm Exam
Variance analysis, cross-table analysis, comparison of the two average
Computer application
Correlation: simple correlation analysis, partial correlation analysis,
Regression analysis: dependent variable definition independent, multi-linear regression
Computer application
Non-parametric tests: Chi square analysis, Mann-U test Withney
Instructors
Assoc. Prof. Lokman Hakana TECER
e-mail
[email protected]
Website
1