M4 - Drawing Conclusions from Data: an Introduction

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.

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 first session 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.

Course prerequisites

The course is open to all. It is necessary to have an understanding of basic algebra (basic rules, solving equations, ...), exponents and square roots.

Exam / Certificate

If you attend all 6 sessions you will receive a certificate of attendance via e-mail after the course ends.

Additionally, you can take part in an exam. If you succeed in this test a certificate from Ghent University is issued.
The exam consists of a take home project assignment. You are asked to write a report by a set deadline.

Micro-credential

This module is part of the micro-credential 'Applied Statistics: from Basics to Regression Modelling' that consists of three modules:

• Module 4 - Drawing Conclusions from Data: an Introduction
• Module 8 - Exploiting Sources of Variation in your Data: the ANOVA Approach
• Module 11 - Explaining and Predicting Outcomes with Linear Regression

If you are planning on registering for all three modules, consider enrolling for the micro-credential instead. Read more...

Type of course

This is an on campus course. We offer blended learning options if, exceptionally, you can't attend a session on campus.

Schedule

November 7, 14, 21 and 28, December 5 and 12, 2023, from 5.30 pm till 9.30 pm

Venue

Faculty of Science, Campus Sterre, Krijgslaan 281, 9000 Gent, Building S9, 3rd floor, Auditorium 3.

Teacher

Dr. Els Adriaens (Adriaens Consulting bvba) studied biology, obtained a PhD in pharmaceutical sciences and a Master in Statistical Data Analysis at Ghent University.

She is consultant in statistical data analysis specialized in the field of the development and validation of alternatives to laboratory animals.

Course material

Access to slides and data files

Book recommendations

A recommended handbook for further study is 'Fundamentals of Biostatistics', Bernard Rosner, 8^th ed. (2015), Thomson Brooks/Cole (ISBN 978-1305268920). The examples used in this book are restricted to the field of bioscience. The book is therefore recommended if you have a background in a related research area, such as (veterinary) medicine, biotechnology, biology, pharmacy, a.s.o.

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. The exam fee is € 35.

Register

Register for this course

UGent PhD students

As UGent PhD student you can incorporate this 'specialist course' in your Doctoral Training Program (DTP). To get a refund of the registration fee from your Doctoral School (DS) please follow these strict rules and take the necessary action in time. The deadline to open a dossier on the DS website (Application for Registration) for this course is October 6, 2023.

Opening a dossier with your DS does not mean that you are enrolled for the course with our academy. You still need to register on the site.

It is you or your department that pays the fee first to our academy. The Doctoral School refunds that fee to you or your department once the course has ended.

Please note that it is not obligatory to participate or succeed in the exam to receive a refund.