Statistics

About the course

Subjects

Statistics Quantitative methods

Course content

The major goal of the statistics course is to produce statistically educated students which mean that students should develop statistical literacy and the ability to think and reason statistically.

Statistics is a valuable tool in the practical application of every other science. Emphasis is on interpretation and understanding of simple statistical methods as applied in business, economics, different types of companies or institutions and industries.

The topics of the curriculum are:

a)The basic laws of probability and the most important probability distributions.

b) Descriptive statistics, both numerical and graphical.

c) Statistical inference; estimators, confidence intervals and significance tests of hypotheses.

d) One and two sample tests for means and proportions; paired and unpaired data.

e) Analysis of association using contingency tables and correlation.

f) Regression analysis; simple, multiple, logistic.

g) One-way and two-way analysis of variance, analysis of covariance.

See course description in course catalogue

What you will learn

The goal is to enable the students to interpret, understand and apply basic statistical concepts as they apply in scientific research as well as in everyday life. The students will become familiar with basic probability theory as a model for randomness, concepts of statistical inference as well as a number of concrete estimators, confidence intervals and test. Statistical software will be introduced. At the completion of this course the students will be able to:

Identify key theories, models and concepts of probability and statistics.
Use graphical and numerical methods for exploring and summarizing data
Describe basic probability and how probability helps us understand randomness in our lives, as well as grasp the crucial concept of a sampling distribution and how it relates to inference methods.
Choose and justify appropriate descriptive and inferential methods for examining and analyzing data and drawing conclusions.
Analysis of the association between categorical, discrete, and continuous variables, using contingency tables, correlation, regressions, and analysis of variance.
Communicate the conclusions of statistical analysis clearly and effectively, i.e identify connections between basic statistics and the real world.

Facts

Level

Bachelor

Type

Mandatory course

ECTS

7.5

Code

BISHO1005U

Teaching periods

Autumn – 1st quarter

Autumn – semester

Academic year

2025/2026

Status

Available places

Teaching language

English

Teaching Format

Hybrid

Exams

Written exam on campus
Individual exam, autumn

Assessment type

7 point grading scale