COVID-19 UPDATE: The safety of our students and staff is our top priority. Therefore, Stats Camp will be holding seminars online via live interactive zoom discussion groups. Our goal is to expand on the interactivity side and provide one-on-one consulting time via virtual breakout rooms. We are offering a discount code to a future camp worth $200 off and we are offering 1-hour of post camp consultation as an added value. Registrations will be accepted up to 12 hours prior to seminar start date and time. All seminars will be conducted in CDT time and will be recorded. The recordings will be made available to you within 3-5 business days of the live recording date. Access will be granted to the recorded videos for 1 year from the date of the seminar. Have questions? Contact us

Bayesian Data Analysis Seminar

Session 1: June 1 – 5, 2020
Albuquerque, NM – Embassy Suites


FAQVenue Info – Hotel Booking
$1,895 Faculty/Professional or $1,145 Student/Post-Doc

Payment Options

Seminar fee includes all materials, downloads, software access, training, refreshments and access to a recorded video of seminar:

Enrollment is open to public, students, graduates and professionals. Save a seat today, pay later.

Statistics Seminar Objectives

After engaging in course lectures and discussions as well as completing the hands-on practice activities with real data, participants will be able to:

  • Explain the difference between frequentist and bayesian statistics
  • Critically evaluate applications of Bayesian analysis in scientific studies.
  • Analyze data using R
  • Specify, estimate, evaluate, and compare different Bayesian models to fit possible hypothesis.

Participants are encourage to bring data of interest to work with during the week, there will be time to work on it with help of the instructor. Work on datasets of interest will magnify the learning and impact of the course.

Participants will also complete the course with a foundation for future learning about Bayesian statistics and knowledge about available resources to guide such endeavors.

Seminar Syllabus

Summer Stats Camp 2020: Bayesian Data Analysis
MondayJune 1, 2020
9:00–10:45Bayesian reasoning generally
10:45–11:00Snack and Refreshment Break
11:00–12:30Perfidious pp values and the con game of confidence intervals
12:30–1:30Lunch Break
1:30–3:15Bayes’ rule, grid approximation, and R; Simple examples to train intuition
3:15–3:30Snack and Refreshment Break
3:30–5:00Markov Chain Monte Carlo and JAGS; Complete programs for Bayesian analysis
5:30~7:30Social “hour” for all Stats Campers
TuesdayJune 2, 2020
9:00–10:45Brief introduction to R and Rstudio
10:45–11:00Snack and Refreshment Break
11:00–12:30Know your distributions. Application of priors
12:30–1:30Lunch Break
1:30–3:15General linear model. Multiple regression, and robust regression
3:15–3:30Snack and Refreshment Break
3:30–5:00General linear model. Robust regression
WednesdayJune 3, 2020
9:00–10:45Model comparison
10:45–11:00Snack and Refreshment Break
11:00–12:30General linear model. T-test and ANOVA
12:30–1:30Lunch Break
1:30–3:15Regularization and polynomials in linear regression
3:15–3:30Snack and Refreshment Break
3:30–5:00Generalized linear Model. Logistic regression
ThursdayJune 4, 2020
9:00–10:45Generalized linear Model: Count regression
10:45–11:00Snack and Refreshment Break
11:00–12:30Multilevel linear regression
12:30–1:30Lunch Break
1:30–3:15Multilevel linear regression
3:15–3:30Snack and Refreshment Break
3:30–5:00Multilevel growth curve/repeated measures
FridayJune 5, 2020
9:00–10:45Introduction to missing data
10:45–11:00Snack and Refreshment Break
11:00–12:30Missing data in Bayesian inference
12:30–1:30Lunch Break
1:30~3:30Individual Consultations

Statistical Methods Seminar Description

Overview: Many fields of science are transitioning from null hypothesis significance testing (NHST) to Bayesian data analysis. Bayesian analysis provides rich information about the relative credibilities of all candidate parameter values for any descriptive model of the data, without reference to p values. Bayesian analysis applies flexibly and seamlessly to complex hierarchical models and realistic data structures, including small samples, large samples, unbalanced designs, missing data, censored data, outliers, etc. Bayesian analysis software is flexible and can be used for a wide variety of data-analytic models. This seminar shows you how to do Bayesian data analysis, hands on.

Instructor: Mauricio Garnier-Villarreal, Ph.D.

Mauricio is a full time professor at Marquette. His Ph.D focus of Quantitative Psychology at the University of Kansas completed in the summer of 2016. His research focus is on the application of Bayesian methods to complex structure data for longitudinal analysis, from both mixed-effects and SEM models. He has experience not only working in the test and development of methods, but also in the application of these in data; in different fields like special education, cognitive decline in aging, healthy aging. He has been involved in the Stats Camp since 2011.

Instructor: Esteban Montenegro, Ph.D.

Esteban is a consultant and researcher for Yhat Enterprises. His PhD focused on Research, Evaluation, Methods and Statistics at Texas Tech University. His research focuses on healthy aging, latent variable modeling and advance applications of Bayesian inference. He has been engaged in different projects form different fields as consultat such as kynesyology, health psychology, interior design, social psychology. Esteban is starting a new position as post-doc researcher at UC Davis Alzheimer’s Disease Center-East Bay.

Seminar Audience

The intended audience is advanced students, faculty, and other researchers, from all disciplines, who want a ground-floor introduction to doing Bayesian data analysis.

Seminar Prerequisites

Required:

  • Basic proficiency in multiple linear regression, the generalized linear model.
  • Intermediate proficiency with at least one statistical software package (e.g., SPSS, Stata, SAS, R, etc.).

Not required but advantageous:

  • At least limited experience (e.g., graduate-level course) with multilevel models
  • Intermediate proficiency in R, or syntax base software

No level of proficiency beyond basic awareness is assumed for skills related to:

  • Bayesian Statistics
  • Data analysis using R

Seminar Topics

  • The rich information provided by Bayesian analysis and how it differs from traditional (Frequentist) statistical analysis
  • The concepts of Bayesian reasoning along with the easy math and intuitions for Bayes’ rule
  • The concepts and hands-on use of modern algorithms (“Markov chain Monte Carlo”) that achieve Bayesian analysis for realistic applications
  • How to use the free software R for Bayesian analysis.
  • An extensive array of applications, including comparison of two groups, ANOVA-like designs, linear regression, logistic regression, multilevel regression, and growth models, count regression, robust regression, regularization and polynomials, and missing data treatments in Bayesian inference.

Install Software Before the Seminar

It is important to bring a notebook computer to the seminar, so you can run the programs and see how their output corresponds with the presentation material.  Please install the software before arriving at the seminar. We’ll be estimating the examples in R languaje using the packages rstan and brms. The latter will be the main package in this course. You can read more about brms package: https://mc-stan.org/users/interfaces/brms.

Seminar Files

Below are links to seminar files for those who enrolled in the seminar. Please download these files onto your computer before the first day of the seminar. The files are password protected to respect the intellectual property rights of the instructors. By using your login information you agree not to share your login information or the content protected by it.

Instructor will provide password on first day of seminar:
Click Here to Access Bayesian Data Analysis Seminar Files

Bayesian Data Analysis Statistics Course

Why Should You Attend?

  • Get 1 on 1 Consultation With Instructor
  • Professional Networking
  • Peer Socializing
  • Collaboration
  • All Seminar Resources
  • Breakfast (Embassy guests), Lunches, & Snacks Daily