# Mathematical Statistics, 6 credits (TAIU06)

Matematisk statistik, 6 hp

### Main field of study

Mathematics Applied Mathematics

First cycle

Programme course

Xiangfeng Yang

### Director of studies or equivalent

Ingegerd Skoglund
Course offered for Semester Period Timetable module Language Campus VOF
6IDAT Computer Engineering, B Sc in Engineering (Software Engineering) 4 (Spring 2017) 2 4 Swedish Linköping v
6IDAT Computer Engineering, B Sc in Engineering (Embedded Systems) 4 (Spring 2017) 2 4 Swedish Linköping v
6IKEA Chemical Analysis Engineering, B Sc in Engineering 4 (Spring 2017) 2 4 Swedish Linköping v
6IMAS Mechanical Engineering, B Sc in Engineering 4 (Spring 2017) 2 4 Swedish Linköping o

### Main field of study

Mathematics, Applied Mathematics

First cycle

G1X

### Course offered for

• Computer Engineering, B Sc in Engineering
• Chemical Analysis Engineering, B Sc in Engineering
• Mechanical Engineering, B Sc in Engineering

### Entry requirements

Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.

### Prerequisites

Calculus, Linear Algebra.

### Intended learning outcomes

This course intends to provide an introduction to mathematical modelling of random experiments and statistical theory/methodology. The course also illustrates applications, in particular within the fields of engineering and science. After completing the course the student should be able to:

• Identify simple experimental situations where random components can influence the result.
• Give an account of fundamental probabilistic concepts, such as random variable and distribution function.
• Construct relevant probabilistic models for simple random experiments.
• Compute important quantities in probabilistic models, such as probabilities and expected values.
• Give an account of fundamental concepts and methods within statistical theory, such as point estimator and confidence interval.
• Choose appropriate methods of analysis and apply these to simple probabilistic models that are constructed from observed data.
• Present conclusions drawn from performed calculations and judge the reasonableness of the conclusions.
• Use statistical software package.

### Course content

Sample space, events and probabilities. Combinatorics. Conditional probability and independent events. Random variables and their probability distributions: exponential, normal, binomial och Poisson distributions. Expected value and standard deviation. Central limit theorem. Descriptive statistics. Point estimation of Expected value and standard deviation. Confidence interval and tests of hypotheses. Chi-square test. Simple linear regression. Engineering applications. Simulation.

### Teaching and working methods

Lectures, problem classes and computer exercises.

### Examination

 LAB1 Computer Exercise U, G 1 credits TENA Written Examination U, 3, 4, 5 5 credits

Four-grade scale, LiU, U, 3, 4, 5

### Department

Matematiska institutionen

### Director of Studies or equivalent

Ingegerd Skoglund

Xiangfeng Yang

### Course website and other links

http://courses.mai.liu.se/Lists/html/TAIU06-ing.html

### Education components

Preliminär schemalagd tid: 42 h

### Course literature

Jonsson, Dag/Norell Lennart: Ett stycke statistik. (Studentlitteratur). Formelsamling i matematisk statistik utgiven av institutionen.
Jonsson, Dag/Norell Lennart: Ett stycke statistik. (Studentlitteratur). Formelsamling i matematisk statistik utgiven av institutionen.