No.: 506.004,
Semester: 3. S[521] and S[524], Type: Lecture/Practical, Hours/Week:
1 SE, ECTS: 1.5
Lecturer
Ernst Stadlober
Johannes Moritz Jirak
Status of the Course
Compulsory course of Computer Science, Software
Development-Economy
Aims and objectives
After successful completion of the course, the students are able
to
work with simple statistical problems. They can do graphical and
numerical representations of data. They know methods based on normal
assumptions and they are in the position to apply adequate methods to
practical problems. They have the knowledge to interpret the outcomes.
Teaching method
The presentation is problem-oriented and motivated by practical
examples.
Assignments are given which should be worked out independently and
presented in
the lecture.
Statistics. Descriptive
Statistics (data and their characteristics, exploratory
graphics), Test Distributions (Chi-Square, Student-t, Fisher-F),
Estimators of Parameters (point estimators, methods of estimation,
confidence intervals), Tests of Parameters (one sample problem, two
sample problem), Simple Linear Regression.
Pre-requisites
Calculus T1.
Teaching aids
Stadlober, E. (2007): Statistik für Informatikstudien, Skriptum,
Institut für Statistik.
Devore, J. L. (2007): Probability and Statistics for Engineering and
the Sciences, Thomson Learning, Belmont.
Fahrmeir, L., Künstler, R., Pigeot, I., Tutz, G. (1999):
Statistik. Der Weg zur Datenanalyse, 2. Auflage, Springer, Berlin.
Lehn, J., Wegmann, H. (2006). Einführung in die Statistik, 5.
Auflage, Teubner, Stuttgart.
Mendenhall, W., Sincich, T. (1995). Statistics for Engineering and the
Sciences, 4th Edition, Prentice Hall, Hertfordshire.
Examination method
Continuous assessment and written exam
Files to download
R-Editor: Tinn-R.exe
R-Program: R-2.8.exe
Data: aimu_info.dat,
Kartoffel.csv
Former
Examinations
Schedule