E-learning Biostatistics for medical sciences, nursing science, health sciences and epidemiology.
In this e-learning course, we introduce the basic principles of biostatistics. The aim of the course is to enable students and researchers to learn to analyse their own data using appropriate statistical methods and interpret the results of their statistical analysis. The topics covered are: descriptive statistics, the principles of statistical testing, tests to compare categorical and numerical variables between groups and univariable and multivariable linear and logistic regression and survival analysis. The theory is accompanied by quizzes and practical exercises in the statistical programs SPSS and R. You can choose whether to perform these exercise using SPSS or R or both. The practical exercises enable students to become familiar with SPSS and/or R.
The module contains 30 to 40 hours of course material, aimed at clinical researchers. By the end of the course, students should be able to understand and be able to perform the most common statistical analyses used in clinical research and to select an appropriate statistical method when analyzing their own data. You can find a detailed description of the content of the e-learning course here.
The course has been developed by the methodologists and statisticians of the Clinical Research Unit (CRU) of the Academic Medical Center (AMC) with SOWISO - a company that develops educational software in the field of mathematics and statistics.
If you want to follow the course, you can register via the appropriate registration form. If you would like to use the course for a group in your own institution, please contact us for more information. Please also Get in touch with us if you have any questions!
Full course consisting of 10 modules
These modules are: descriptive statistics; principles of statistical testing; comparing numerical data; comparing categorical data; correlation and linear regression; multiple linear regression; logistic regression; survival analysis - Kaplan-Meier; survival analysis - Cox regression; and repeated measurements.
Study load: 30 – 40 hours
Course fee: € 365,-
A course of the first five modules
These modules are: descriptive statistics; principles of statistical testing; comparing numerical data; comparing categorical data; and correlation and linear regression.
Study load: 15 – 20 hours
Course fee: € 215,-
Global course goals
In the e-learning course Practical Biostatistics, we introduce the basic principles of biostatistics. The aim of the course is to enable you to learn to analyse your own data using appropriate statistical methods and interpret the results of your statistical analysis. The topics covered include: descriptive statistics, the principles of statistical testing, tests to compare categorical and numerical variables between groups and univariable and multivariable linear and logistic regression and survival analysis. The theory is accompanied by quizzes and practical exercises in the statistical programs SPSS and R. These practical exercises take up about half of the study time. You can choose whether to perform these exercise using SPSS or R or both. The practical exercises will enable you to become familiar with SPSS and/or R.
Goals per module
Module 1. Descriptive statistics
In this module, you will become familiar with the definitions of different types of data. You will learn how to choose appropriate measures of location and spread to describe your data and calculate them. You will also learn how to decide whether a variable can be described using a normal distribution.
Module 2. Principles of statistical testing
In this module, you will learn about the most important properties of the normal distribution and how the standard deviation and the standard error can be used to describe samples and populations. You will also calculate and interpret standardized scores, construct a confidence interval around an estimate and understand the link between confidence intervals and p-values.
Module 3. Comparing numerical data
In this module, you will learn how to decide which statistical tests to use when comparing two or more groups without correcting for other variables. You will learn about the t-test, one-way analysis of variance (ANOVA), the Mann-Whitney U test and the Kruskal-Wallis test.
Module 4. Comparing categorical data
In this module, you will learn how to test whether proportions differ between groups and whether two categorical variables are statistically associated. You will learn about the two-by-two contingency table, Fisher exact test, the Chi-squared test, the risk ratio and the odds ratio. The risk ratio and odds ratio are measure of the strength of an association between binary variables.
Module 5. Correlation and linear regression
In this module, you will learn about correlation and linear regression. You will learn how to calculate and interpret Pearson’s and Spearman’s rank correlation and how to use univariable linear regression.
Module 6. Multiple linear regression
In this module, you will learn how to use linear regression with multiple independent variables, when and how to use interaction terms and how they can be interpreted and how to use categorical independent variables. You will also learn which assumptions are required when using linear regression and how predictors can be selected in a multivariable model.
Module 7. Logistic regression
In this module, you will learn how to use logistic regression. Logistic regression is used when you have a binary dependent variable. You will also learn about the relationship between the logistic regression coefficients and the odds ratio and how to interpret logistic regression coefficients for categorical and continuous predictors.
Module 8. Survival analysis - Kaplan-Meier
In this module, you will learn to describe and analyse censored numerical data. You will learn how the definitions of survival analysis and censored data and how to obtain and interpret a Kaplan-Meier survival curve. You will also learn to compare survival curves for different groups statistically using the log-rank test.
Module 9. Survival analysis - Cox regression
In this module, you will learn the basic principles of the Cox regression model, including what a hazard ratio is. You will also learn how to interpret the regression coefficients resulting from this model, what the assumptions of the Cox model and how to assess these. Finally, you will obtain insight into the similarities between the Cox model, the linear model and the logistic model.
Module 10. Repeated Measurements
In this module, you will learn what repeated measurements are, how they can be recognized, why they are useful and why incorrect analysis of repeated measurements can lead to incorrect conclusions. You will also learn how to use several simple statistical solutions that can be used in some situations and some general considerations, such as data format and missing values.
FAQ on the e-learning course Practical Biostatistics
Q: What is the target audience of the course?
A: The course can be used by medical specialists, fellows, research nurses, PhD- and undergraduate students. The course assumes understanding of the English language and a basic knowledge of medical research methodology and secondary school level mathematics are required.
Q: What is the study load of the course?
A: The ten modules of the course require approximately 30 to 40 hours of study, depending on the student’s previous experience of statistics. Students can also choose to only follow the first five modules of the course, this requires approximately 15 to 20 hours of study.
Q: How is the theory presented?
A: The theory is presented in slide shows and short texts. The slide shows contain text, formulas, illustrations and animations and are accompanied by a voice-over. It is possible to view the complete voice-over script. The number of slides in each slide show varies, but is always less than 20.
Q: What kind of exercises does this course contain?
A: There are exercises to help you understand the theory, interpretation and application of the statistical methods after some of the slide shows. There are a variety of types of exercises. Each chapter contains a set of SPSS exercises and a set of R exercises. These are broadly similar, but not identical. The SPSS and R exercises explain how to apply the statistical methods in practice using an example dataset. The exercises contain tutorials on the use of SPSS and R. Students can choose to complete either the SPSS or R exercises or both.
Q: Our institute does not use SPSS. Can we still use the course?
A: The course contains tutorials on and exercises using SPSS and R. Everyone can download the R statistical environment for free. In addition, most Dutch research institutions have a contract with SURFspot for reduced price home versions of SPSS.
Q: As a teacher, can I keep track of the progress made by the course-participants?
A: Yes, a teacher or administrator can view the progress made by all course participants.
Q: What kind of software do you need to view the course?
A: The course is web-based and can be accessed anywhere in the world via an internet connection and web browser, such as Chrome. You will need either SPSS or R installed on your computer to be able to carry out the practical exercises.
Q: Who will provide technical support?
A: For individual applicants, support is provided through the course forum and through the e-mail address email@example.com.
The Clinical Research Unit (CRU), founded in 2006, is an academic research support department providing a range of services to clinical researchers in the AMC, such as data management, quality control, and methodological and statistical support.
SOWISO is founded in 2010 as a spin-off from the Technical University of Eindhoven. SOWISO develops state-of-the-art e-learning solutions for educational institutions and publishers.
Please contact us for more information
If you have questions on the course content, pricing, implementation and customization of the course or on the experiences of the AMC in using this course, please e-mail: firstname.lastname@example.org