Drawing Conclusions from Data: an Introduction

Description

This course aims to provide insight into basic statistical concepts with emphasis on practical applications. Mathematical formulae will be kept to a minimum. The theory and the methods of analysis will be extensively illustrated with examples relating to a wide variety of different fields. To emphasize the practical approach in this course all classes will take place in a pc room.

The practical part of the first session (after the break) will be dedicated to getting to know the software package R. Participants are encouraged to participate in both parts.

We start with concise graphical and numerical descriptions of data obtained from observational or experimental studies. The most common and frequently used probability distributions of discrete and continuous variables will be presented. Statistical inference draws conclusions about a population based on sampled data. Chance variations are taken into account such that a level of confidence is attached to these conclusions.

We present the reasoning behind significance tests for the comparison of observed data with a hypothesis, the validity of which we want to assess. We apply this procedure to data obtained either from one or from two populations.

The correct use of the t-test will be discussed. Nonparametric methods are considered as a possible alternative in case the requirements of the t-test are not met.

We cover the basic concepts of hypothesis testing for categorical data, including the chi-square test.

Quite often the relationship between two variables, where the outcome of one variable is seen as depending on the value of the other, is the focus of scientific interest.

We will give an introduction to linear regression analysis, where a regression line based on observations obtained in a sample describes this relation.

Hands-on exercises are worked out behind the PC using the R software.

Target audience

This course will benefit professionals and investigators from diverse areas, research scientists, clinical research associates, investing in data handling and wishing to acquire insight into basic statistical methods or to refresh their knowledge and practice of statistics.

Fees

The participation fee is 1320 EUR for participants from the private sector. Reduced prices apply to students and staff from non-profit, social profit, and government organizations. An exam fee of 35 EUR will be applied.

• Industry, private sector, profession*: € 1320
• Non profit, government, higher education staff: € 990
• (Doctoral) students, unemployed: € 595

*If two or more employees from the same company enrol simultaneously for this course a reduction of 20% on the course fee is taken into account starting from the second enrolment.

Registration

More information and registration on our Beta-Academy website.