# 107.254 Statistics and Probability Theory This course is in all assigned curricula part of the STEOP.\$(function(){PrimeFaces.cw("Tooltip","widget_j_id_20",{id:"j_id_20",showEffect:"fade",hideEffect:"fade",target:"isAllSteop"});});This course is in at least 1 assigned curriculum part of the STEOP.\$(function(){PrimeFaces.cw("Tooltip","widget_j_id_22",{id:"j_id_22",showEffect:"fade",hideEffect:"fade",target:"isAnySteop"});});

2020W, VO, 2.0h, 3.0EC

## Properties

• Semester hours: 2.0
• Credits: 3.0
• Type: VO Lecture
• Format: Distance Learning

## Learning outcomes

After successful completion of the course, students are able to:

• Use basic counting techniques (multiplication rule, combinations, permutations) to compute probability.
• Compute conditional probabilities directly and using the Bayes theorem, and check for independence of events.
• Set up and work with discrete random variables. In particular, understand the Bernoulli, binomial, geometric and Poisson distributions.
• Work with continuous random variables. In particular, know the properties of uniform, normal and exponential distributions.
• Know what expectation and variance mean and compute them.
• Understand the law of large numbers and the central limit theorem.
• Compute and interpret descriptive statistics and plots.
• Compute confidence intervals for estimators.
• Carry out  and interpret hypothesis testing (t-tests, ANOVA, chi^2-test, Frequncies), and compute and interpret the p-value.
• Compute and interpret the correlation between two variables.
• Compute and interpret univariate linear regression models.
• Use statistical software R to implement the statistical analysis methods covered in the course.

## Subject of course

This course is an introductory statistics and probability theory course.

• Counting (permutations, combinations)
• Compute probabilities
• Random variables, distributions (Bernoulli, binomial, geometric, Poisson, uniform, normal and exponential distributions), quantiles, mean, variance,covariance, correlation, independence
• Conditional probability, Bayes' theorem
• Law of large numbers, Central limit theorem
• Sampling
• Descriptive Statistics (elementary statistics, frequency table, diagrams, empirical distribution, histograms)
• Significance tests and confidence intervals, analysis of variance, univariate linear regression

## Teaching methods

Lectures and accompanying exercises in the exercise sessions. In the lecture central concepts will be presented, which will be then practiced and deepened in the exercise sessions on the basis of case studies. Exercises will involve solving problems and the use of R for computation, simulation and visualization.

## Mode of examination

Written

For students of Informatics.

# Requirements for participation:

1. Registration in the course via the corresponding TISS page within the registration period.
2. Successful completion of STEOP.
3. Basic knowledge of linear Algebra and Calculus.

## Course dates

DayTimeDateLocationDescription
Thu08:00 - 10:0008.10.2020 - 28.01.2021HS 11 Paul Ludwik VO 107.254
Statistics and Probability Theory - Single appointments
DayDateTimeLocationDescription
No records found.

## Examination modalities

Result of the final written exam. The exam is a multiple-choice questions exam. For each task, there are four possible answers, and only one is correct. The one alternative that best completes the statement or answers the question should be chosen by ticking. Ticking more than one answer leads to the question being marked as incorrect. You have to use a pen with either blue or black ink. The processing time is 90 minutes. You may use a non-programmable calculator and a hand- written sheet with the formulas you may need (written on one two-sided A4 format paper). Please note that a copy of a handwritten sheet is not a handwritten sheet and cannot be used in the exam. The sheet with formulas should be submitted with the exam. Computers, smartphones, tablets, notes, books, etc., as well as discussions and consultations, are not allowed during the exam. It is mandatory to bring a personal document/ID with picture.

## Exams

DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Tue14:00 - 16:0026.01.2021Informatikhörsaal written05.01.2021 12:00 - 20.01.2021 18:00TISS1. Prüfungstermin W2020
Tue14:00 - 16:0026.01.2021FH Hörsaal 1 - MWB written05.01.2021 12:00 - 20.01.2021 18:00TISS1. Prüfungstermin W2020
Tue14:00 - 18:0026.01.2021EI 9 Hlawka HS -MWB written05.01.2021 12:00 - 20.01.2021 18:00TISS1. Prüfungstermin W2020
Mon14:00 - 16:0001.03.2021Informatikhörsaal written05.02.2021 07:00 - 21.02.2021 23:55TISS2. Prüfungstermin W2020
Mon14:00 - 16:0001.03.2021FH Hörsaal 6 - TPH written05.02.2021 07:00 - 21.02.2021 23:55TISS2. Prüfungstermin W2020
Mon14:00 - 18:0001.03.2021FH Hörsaal 5 - TPH written05.02.2021 07:00 - 21.02.2021 23:55TISS2. Prüfungstermin W2020
Mon14:00 - 16:0007.06.2021FH 8 Nöbauer HS - MATH written03.05.2021 07:00 - 28.05.2021 18:00TISS3. Prüfungstermin W2020
Mon14:00 - 16:0007.06.2021FH Hörsaal 5 - TPH written03.05.2021 07:00 - 28.05.2021 18:00TISS3. Prüfungstermin W2020
Mon14:00 - 16:0007.06.2021FH Hörsaal 6 - TPH written03.05.2021 07:00 - 28.05.2021 18:00TISS3. Prüfungstermin W2020

## Course registration

Begin End Deregistration end
31.08.2020 07:00 20.09.2020 18:00 24.09.2020 18:00

## Curricula

Study CodeSemesterPrecon.Info
033 526 Business Informatics 3. Semester
Course requires the completion of the introductory and orientation phase
033 532 Media Informatics and Visual Computing 3. Semester
Course requires the completion of the introductory and orientation phase
033 533 Medical Informatics 5. Semester
Course requires the completion of the introductory and orientation phase
033 534 Software & Information Engineering 3. Semester
Course requires the completion of the introductory and orientation phase
884 Subject: Informatics und Informatics Management 5. Semester
Course requires the completion of the introductory and orientation phase

## Literature

Literature will be discussed in the first lecture.

## Previous knowledge

see above (requirements)

English