Course Bayesians statistics and JASP


Location: Erasmus MC

Click here for details of programme
Click here to register for this course


Course Bayesians statistics and JASP

Bayesian statistics is a branch of statistics in which evidence is expressed as a measure of uncertainty instead of frequency (i.e., p value). It allows the scientist to update initial beliefs about the true state of the world (e.g., null or alternative hypothesis) with observations, reducing uncertainty when more data is collected. Instead of only testing your data under the null hypothesis, Bayesian statistics enables the scientist to assess the likelihood of both the null and the alternative hypothesis. With Bayesian statistics, you can finally distinguish between absence of evidence and evidence of absence!

 JASP is a new, free, and user-friendly alternative to SPSS. It runs on Windows, Mac OS X, and Linux; it is open source; it is easy to use; and it features all conventional parametric analysis for both frequentist and Bayesian statistics.

What JASP has to offer:

  • It is free
  • It is open source
  • Data, analysis, and output in a single window
  • It has a clear and intuitive interface
  • It allows alteration on analysis after execution (SPSS requires you to redo the analysis if you want to make alterations).
  • It offers both Frequentist and Bayesian statistics
  • It produces formatted tables that can be easily copy-pasted to your manuscript. 

What Bayesian statistics have to offer:

  • Bayesian statistics makes use of a more intuitive form of probability, uncertainty instead of proportions of values under a hypothetical distribution (p-values).
  • It can incorporate prior beliefs, knowledge, or results of parameters in the analysis.
  • It enables comparison of the likelihood of the alternative hypothesis in relation to the null hypothesis as an odds ratio (instead of testing only the null hypothesis in frequentist statistics).
  • Results are not based on unobserved data (Frequentist statistics assume hypothetical data under the null hypothesis).
  • Is not influenced by sampling design and allows for continual data collection until either the null or the alternative hypothesis is acceptably likely.
  • No inflation of Type I error rate due to multiple comparisons (i.e., no more Bonferroni correction). 

Aim of the course

After this course the participants will have a basic understanding of Bayesian statistics and inference; they will feel at home with the statistical software package JASP; and will be able to confidently use basic and more advanced statistical analysis using both frequency and Bayesian statistics.

 Requirements of the workshop

Basic knowledge of statistics is required and some knowledge of data analysis in a statistical software package (e.g., SPSS, R, Excel) is recommended. 
Also, a laptop with working internet-connection is required for the tutorials with administrative access to download data and install software.

If possible, bring your own dataset, because part of the last tutorial is reserved to use Bayesian statistics on your own research data.

ECTS 
This course is 0,3 ECTS

Course content

This one-day course will take 7 hours and consists of four modules: two lectures and two tutorials.

 Lecture #1

  • Introduction to inference using Bayes Theorem
  • Difference between Bayesian statistics and frequentist statistics
  • Benefits and uses of Bayesian statistics
  • Bayesian hypothesis testing, Bayes Factor
  • Frequentist and Bayesian statistics in JAPS: t-test, ANOVA

Timetable

9.30 - start

09.30 - 11.00 | lecture 1
11.15 - 13.00 | tutorial 1
13.00 - 14.00 | lunch
14.00 - 15.30 | lecture 2
15.45 - 17.15 | tutorial 2

17.15 - end

Tutorial #1

  • Getting to know JASP
  • Descriptive statistics, correlation tables, contingency tables
  • Performing t-test and ANOVA exercises with both frequentist and

Bayesian statistics

Lecture #2

  • Further explanation of Bayesian statistics
    • Informative and weak priors
    • Power and sampling
    • No more Bonferroni corrections
  • More Frequency and Bayesian statistics in JASP:
    • Repeated measures ANOVA
    • ANCOVA
    • Linear Regression

Tutorial #2

  • Working with Frequency and Bayesian statistics in JASP:
    • Repeated measures ANOVA
    • ANCOVA
    • Linear Regression
  • Performing Bayesian analyses on your own dataAttendance fees

    The subscription fee of non-commercial participants for the Course is €200. 
  • All participants from the Postgraduate School MolMed get a discount of 100 % 
  • PhD students and research master students have 50% discount 
  • Research master students who pay it themselves have 75% discount 

 

 

General information
Financial regulation of the Postgraduate School MolMed

From January 1st, 2017 the following financial rules apply, but they may differ per course still. Look at the course fee of each course to be sure which discounts are really applied:

Non-commercial course, symposium or workshop fee: €200/day, €750/week

• Participants of the postgraduate school MolMed: discount of 100%

• However, the Research Management course and the workshops Photoshop/Illustrator/Indesign have to be paid from the ‘personal budget’ of employees, MolMed members and PhD students included. So they will receive an invoice from us which you have to pay and which will be reimbursed by your Department. When you will pay from your personal budget you need to provide us your home address details for the invoice

• PhD students and Master’s students, regardless of institution: discount of 50%.

  • The course fees of research master’s students will be paid by their master program at rate of €100/ECTS. For not I&I master students: please inform your master program in advance whether they agree to pay.
  • Master’s students who are paying the fee from their private budget: discount of 75%. When you will pay from your personal budget you need to provide us your home address details for the invoice.
  • However, 2 courses in statistics are paid centrally by the Dept. of Research policy for all PhD students from Erasmus MC! These are R and the SPSS course. So for Erasmus MC PhD students, these courses are always free, provided you are officially registered as a PhD student.

There is one fee for the entire course. There is no reduction for partial participation.

Some courses have less course days: SPSS 3 days, Survival Analysis 2 days, Management 2 days, Presenting 1,5 days and also other may be shorter as indicated on the website.

Commercial participants, companies & sponsors are invited to inquire about commercial tuition fees and about sponsoring.

All invoices will be sent by email to the mail address that you filled in upon registration. If this address is not correct we use your Erasmus MC address.

Those who register for a course, symposium or workshop agree with these financial conditions.

 


 

 

 

 

 



Click here for details of programme
Click here to register for this course


Click here for the other items