Statistical Methods

2019-2020

Course Objective

After this course, the student should be able to:
- summarize data graphically and numerically, to describe the most
important characteristics of the data, and to find a suitable model
distribution,
- make probabilistic manipulations and calculations, calculate an
expected value, and to explain and apply the law of large numbers and
the central limit theorem,
- calculate and interpret confidence intervals in one- and two-sample
problems for means or proportions,
- test hypotheses about means and proportions in one- and two-sample
problems and to interpret the outcome,
- conduct a correlation and linear regression analysis (i.e. estimating
and testing), to predict, and to interpret the results,
- use the chi-square test for categorical data in various fields of
application, explain his/her choice, and interpret the results.

Course Content

- Summarising data;
- Basics of probability theory;
- Estimating means and fractions;
- Hypothesis testing for one- and two-sample problems about means and
proportions;
- Correlation and linear regression;
- Contingency tables.

Teaching Methods

Lectures (10x2 hours; in general, two lectures per week),
exercise classes (6x2 hours; in general, once per week),
and computer classes (6x2 hours; in general, once per week).
Attendance to all lectures and classes is not mandatory but strongly
recommended.

Method of Assessment

Mandatory (group) assignments and exams (midterm and final, both
mandatory).
You will work on assignments during weekly computer classes.
In the case that one of the exams (midterm or final) is not passed, a
resit exam can be taken which covers the whole lecture material.
The final grade consists of the following components (with the indicated
weights): the exam grade (75%) and the average assignment grade (25%).
The exam grade is either the weighted average of the midterm exam grade
(40%) and the final exam grade (60%), or it is the resit exam grade
(100%).
Both, the exam grade and the average assignment grade have to be at
least 5.5 in order to pass the course.
If the resit exam is written, the homework assignment grades still count
towards the final course grade as explained above.
If both partial exams are passed, then doing the resit exam is not
possible anymore.
There is no resit possibility for the assignments.

Literature

Mario F. Triola "Elementary Statistics" Twelfth Edition (Pearson New
International Edition) ISBN 978-1-292-03941-1

Target Audience

2CS, 2LI, 2IMM

Recommended background knowledge

Basic mathematical knowledge; this includes fractions, square-roots,
sums, and simple manipulations of equations.

General Information

Course Code X_401020
Credits 6 EC
Period P2
Course Level 200
Language of Tuition English
Faculty Faculty of Science
Course Coordinator dr. D. Dobler
Examiner dr. D. Dobler
Teaching Staff dr. D. Dobler

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Seminar, Lecture, Practical
Target audiences

This course is also available as: