M3-Drawing Conclusions from Data: an Introduction
AI and Data Science
AI and Data Science
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.
Fees and registration form are available on the website of the Academy for Lifelong Learning of the Faculty of Sciences (UGent).
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.
The course is open to all. It is necessary to have an understanding of basic algebra (basic rules, solving equations, ...), exponents and square roots.
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.
This is an on campus course. We offer blended learning options if, exceptionally, you can't attend a session on campus.
November 8, 15 and 29, December 6, 13 & 20, 2022, from 5.30 pm till 9.30 pm (Note: there is no class on November 22.)
Faculty of Science, Campus Sterre, Krijgslaan 281, building S9, 9000 Gent.
Access to slides and data files
A recommended handbook for further study is 'Fundamentals of Biostatistics', Bernard Rosner, 8th 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.
This module is part of the microcredential 'Applied Statistics: from Basics to Regression Modelling' that consists of three modules:
If you are planning on registering for all three modules, consider enrolling for the microcredential instead. Read more...