Learning Bayesian Statistics

#35 The Past, Present & Future of BRMS, with Paul Bürkner

Mar 12, 2021
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1
Introduction
00:00 • 2min
2
The Learning Patient Statistics Podcast
02:11 • 2min
3
How Does It Feel to Be Star?
04:18 • 3min
4
How Mathematical and Statistic Analysis Meets?
06:50 • 2min
5
Agas, That's Superinteresting Research, Right?
08:32 • 2min
6
Stutcar Aen Yuis, I Want to Teach Bas Statistics
10:44 • 2min
7
How Did You Come to R and Sten?
13:00 • 2min
8
B R Ms - What Is It?
15:27 • 3min
9
Is Baramis a Good Regression Tool?
18:25 • 2min
10
Is It a Requested Model?
19:57 • 2min
11
Aramis
21:54 • 2min
12
How Did You Fit That Work Into Your PhD?
23:25 • 2min
13
I'm Glad That This Kind of Stuff Cant Happen
25:41 • 2min
14
Is There a Non Linear Relationship?
27:15 • 2min
15
Predicting the Future Using Spine Processes
29:03 • 3min
16
How to Braya?
32:05 • 2min
17
Are You Afraid of Reviewers?
34:35 • 3min
18
Beramis and Its Main Weaknesses
37:49 • 4min
19
Is There a Better Year Than 20 20?
41:45 • 3min
20
Aspects of Prior Selection in a Regression Model
45:02 • 4min
21
How to Choose a Prior on the Latent Scale
48:48 • 2min
22
Is the Prior on the Joint Distribution a Good Prior?
50:23 • 3min
23
How Much Do I Have to Change the Prior to Change a Decision?
53:05 • 2min
24
Is There a Machine Assisting Thet Basion Workflow?
55:09 • 2min
25
The Human Factor
57:38 • 4min
26
What Would You Do if You Had Unlimited Time and Resources?
01:01:54 • 3min
27
The Learn Invasion Statisic Pud Gast Podcast
01:04:26 • 3min