# Statistics and Data Analysis

## General information

The Bachelor's degree programme of Statistics and Data Analysis is intended for students who are interested in mathematical-statistical methods of bulk data analysis and their applications in other areas using computer technology. Students are introduced to the principles of relevant mathematical and statistical methods essential for solving particular real life problems. The aim of the studies is to offer an overview of the basic mathematical-statistical and computer science branches employed for data analysis and processing. The second aim is to provide the students with basic skills necessary for the statistical analysis and computer processing of data files that are employed in various areas of human activities.

The goal of the Bachelor's degree programme is to provide the students with real education focusing on applied mathematics and prepare them for the follow-up studies in the Master's degree programmes.

### A successful graduate is able to

- master the basic knowledge of theory and methodology of mathematical statistics, numerical mathematics, and other mathematical branches
- implement theoretical and practical knowledge of mathematical statistics and numerical mathematics in the selected programming languages (R, MATLAB, STATISTICA, and SAS)
- select appropriate mathematical and statistical procedures and models for the analysis of real data
- interpret and assess data on the basis of obtained theoretical and practical knowledge, and identify hidden connections and relations between phenomena

## Graduate employment

The graduates obtain a good overview of the modern methods used in the analysis of bulk data, especially parametric and non-parametric statistical methods and spectral methods, and will be able to choose appropriate statistical and analytical tools for solving investigated problems. They will be able to modify and develop these methods, create the corresponding software, and analyse the information contained in the data files of various types. The graduates will find employment in research and educational institutions, financial, banking, insurance companies, public administration bodies, in production and business areas, in services and bodies cooperating with the European Union in solving interdisciplinary problems, especially in the areas of economics, banking, insurance, biometrics, environment, and other natural scientific and technical branches. The graduates will be able to teach statistics at universities. Some graduates will continue in the tertiary education (doctoral studies leading to the doctoral degree) in the degree programmes of statistics or related branches. The obtained training in the study programme of Statistics and Data Analysis is so universal that the graduates will be ready to adapt to various activities.

Faculty | Faculty of Science |
---|---|

Type of study | bachelor's |

Mode | full-time |

Standard length of studies | 3 years |

Language of instruction | czech |

## Field of study combinations

#### Field combinations with Statistics and Data Analysis

This field of study is only offered in single-subject study mode

## Admission Requirements

The Learning Potential Test (Czech only)

##### Recommended literature

Passing the Learning Potential Test is not based on any special reading. Examples of previous years' tests can be found on http://www.muni.cz/study/admission/tsp

##### Evaluation criteria

1255The Learning Potential Test results

## Frequently enrolled courses

Recommended study plans and other information can be found in the faculty study catalouge.

### 1st semester

### 2nd semester

### 3rd semester

- Mathematical Analysis III
- Probability and Statistics I
- Mathematical Software
- Examination in English for Specific Purposes - Science
- Electronic Typesetting and Publishing with TeX
- Linear Algebra and Geometry III
- Database Systems
- Finnish for Beginners I
- European Union - basic facts and milestones
- Basic numerical methods
- English for Mathematicians I
- Linear Algebra and Geometry I
- Discrete mathematics
- Introduction to Programming I
- Linear Algebra and Geometry II
- Introduction to Programming II
- Probability and Statistics II
- Numerical Methods I
- Graph Theory
- Mathematics of Insurance
- Computational statistics
- Non-linear dynamics
- Computer Network Services
- Database System Applications
- Chapters from World Literature for Youth
- Physical Education - Football

### 4th semester

- Numerical Methods I
- Probability and Statistics II
- Selected Topics in Mathematical Analysis
- Mathematics of Insurance
- Functional Analysis I
- Mathematics around Us
- Linear Algebra and Geometry II
- Finnish for Beginners II
- Correct Writing for students of disciplines other than Czech
- Stress management, coping (theory & practice)
- English for Mathematicians II
- English for Mathematicians IV
- Mathematical Analysis II
- Mathematics of Finance
- Mathematical Seminary II
- Computer Algebra Systems
- Introduction to Programming II
- Database System Applications
- Physical Education - Pilates
- Physical Education - Volleyball

### 5th semester

- Ordinary Differential Equations I
- Bachelor Thesis 1 (M - neučitelské obory)
- Markov chains
- Linear Algebra and Geometry III
- Linear Models in Statistics I
- Numerical Methods II
- Examination in English for Specific Purposes - Science
- Database Systems
- Classical Mythology: Gods
- Film Projection I.
- Introduction to programming in Python
- English for Mathematicians III
- Probability and Statistics II
- Graph Theory
- Computational statistics
- Functional Analysis I
- Data mining I
- Computer-Systems Architectures
- Computer Network Services
- Information policy and SIS of Czech Republic
- Basics of Fine Art I
- Physical Education - Swimming
- Big Data with SQL

### 6th semester

- Computational statistics
- Linear Models in Statistics II
- Bachelor Thesis 2 (M - neučitelské obory)
- Data mining I
- State examination Bc, Mathematics
- Functional Analysis I
- Mathematics around Us
- Probability and Statistics II
- Numerical Methods I
- Introduction to Machine Learning
- NoSQL Databases
- Relational Database System Architecture
- Database System Applications
- Physical Education - Hiking

#### Additional information