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index.qmd
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---
engine: knitr
---
# Preface {.unnumbered}
::: {.callout-note style="color: blue;"}
#### This is work in progress: about 95%.
:::
This Quarto book collects my personal notes, trials and exercises of the
[Bayesian Statistics the Fun Way: Understanding Statistics and
Probability With Star Wars, LEGO, and Rubber
Ducks](https://nostarch.com/learnbayes) by Will Kurt [@kurt2019].
## About My Motivation for this Quarto Book {#sec-book-motivation}
I am not an expert in statistics. During my study in sociology back in
1970er I had only rudimentary learned about
`r glossary("frequentist statistics")`. There weren't computer only via
time-sharing and keypunching for card-to-tape converter available. This
was painstaking and not motivating because it had not much practical
values. 10 years later I worked sometimes with SPSS but used --- as many
of my colleagues --- the "statistics all" option without much
understanding. It was no fun and so I dedicated most of my time to
theoretical work and later sometimes to qualitative social research via
[grounded theory](https://en.wikipedia.org/wiki/Grounded_theory).
Only when I heard 2015 about R and began to exerpiment with it, I
started my self-directed education in statistics again. Still I was not
so intrigued by Null Hypothesis Statistical Testing (NHST) but more from
Data Science. I noticed the problems with p-values and was therefore
fascinated with [Introduction to the New
Statistics](https://thenewstatistics.com/itns/) by Geoff Cumming &
Robert Calin-Jageman [@cumming2017]. Instead of concentrating on
p-values the book teaches the importance of
`r glossary("confidence interval","confidence intervals")`, (CIs). But
at that time I came across some discussion about
`r glossary("Bayesian statistics")`. I read [The Theory That Would Not
Die](https://www.jstor.org/stable/j.ctt1np76s): How Bayes' Rule Cracked
the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant
From Two Centuries of Controversy by Sharon Bertsch McGrayne
[@mcgrayne2011] but didn't understand at that time how Bayesian
statistics works.
The real game changer for me then was [Statistical
Rethinking](https://www.routledge.com/Statistical-Rethinking-A-Bayesian-Course-with-Examples-in-R-and-STAN/McElreath/p/book/9780367139919)
by Richard McElreath [@mcelreath2020]. I immediately started [my first
Quarto book](https://bookdown.org/pbaumgartner/sr2-notes/) with notes
about the book and the companion bookdown website [*Statistical
rethinking* with brms, ggplot2, and the tidyverse: Second
edition](https://bookdown.org/content/4857/) by A Solomon Kurz. But
unfortunately after four chapters I noticed that I am lacking basic
knowledge and looked around for other books on Bayesian statistics that
are easier to digest for me. I tried A Student's Guide to Bayesian
Statistics by Ben Lambert [@lambert2018], but I stopped reading it after
chapter eight. I has to much theory for me and I was missing the
opportunity trying my own hands out with R.
So finally I came around to Will Kurt's book. I understand that the
modern simulation methods like MCMC are not in the focus of the book and
also the usage of R code is distributed very sparsely in the book. But I
learned (and understood) many Bayesian concepts and could all the
graphics in the book --- where the R code is missing --- replicate with
{**ggplot2**} [@ggplot2] in tidyverse [@tidyverse] style. The book was
at the time (September/October 2023) a perfect match for my rudimentary
knowledge. I have now more trust to continue with Statistical Rethinking
or --- as a possible alternative --- to start with a new Quarto book on
[Doing Bayesian Data Analysis: A Tutorial With R, JAGS, and
Stan](https://sites.google.com/site/doingbayesiandataanalysis/)
[@kruschke2014] which I have already read and (I believe) mostly
understood.
Another motivation to write a Quarto book was to learn how to use
[Quarto](https://quarto.org/). I already wrote some books with bookdown
[@bookdown] but Quarto was relatively new for me. This book was
therefore a good occasion to learn and experiment with the functionality
of Quarto.
## Content and Goals of this Book {.unnumbered}
This book collects personal notes during reading of [Bayesian Statistics
the Fun Way](https://nostarch.com/learnbayes) by Will Kurt. Additionally
I am using [C: Answers to
Exercises](https://nostarch.com/download/resources/Bayes_exercise_solutions_new.pdf)
Each chapter of the book has three main parts:
### Short summaries of the book content {.unnumbered}
This summarizes my own highlights but gives also the necessary
information for my section about "Experiments". Mostly I quote the text
but without page references. Often I made minor editing (e.g., shorting
the text) or put sometimes the content in my own wording. As I follow
the text section by section reader can easily find the quoted passage.
Almost all of my text of this first part of the Quarto book are not
mine, but is coming from the resources mentioned above. There are two
exceptions:
- Whenever necessary I include personal notes already in this part of
the chapter. Most of the time it is combined with a cross reference
to the third main part of the book: my experiments.
- Sometimes there is also base R Code by the author provided. Whenever
possible I convert this base R code by the author in {**tidyverse**}
code.
- I copied all figures into the text as a template for my own
replication.
::: callout-important
Although I have quoted many passages from the original as highlights for
me to remember, this Quarto ebook is not meant to stand alone. My
summaries are driven by my personal interests and my huge gaps in my
statistical knowledge and especially in Bayesian statistics. My notes
are therefore in no way a substitute for Will Kurt's book [Bayesian
Statistics the Fun Way: Understanding Statistics and Probability With
Star Wars, LEGO, and Rubber Ducks](https://nostarch.com/learnbayes) by
Will Kurt [@kurt2019]. Please buy the book so that you can embed my
notes appropriately in the general argumentation of the author.
:::
### Exercises {.unnumbered}
Again I quote the full question text and then try my own solution. If my
solution is not correct or I cant find a solution I will note this in a
personal callout and will correct the solution. If my solution is
correct but with a different method I will also reflect on the result,
but will not adapt or change my solution.
### Experiments {.unnumbered}
Here I am trying to make my own exercises. Most of the examples are
replications of the book figures because the author has not included the
R code. Additionally I cross referenced to the figure from the first
part, the author section. If you hover over the cross reference link you
will get the authors figure overlaid and can compare it with my
replication.
Writing my own R chunks I am using the tidy approach with the collection
of the {**tidyverse**} packages, especially with {**ggplot2**} for the
figures. But instead of using the `library()` command I always mention
the used packages explicitly. Whenever I used another packages I called
the function with the package name in front with the syntax
`<package name>::<function name>()`, like `ggplot2::gplot()`. This is
tedious work but it helps me to learn & remember which command "belongs"
to which package. Only exception is the {**patchwork**} package, as I do
not know how to call commands like `p1 + p2` with the package name.
In graphics I use not only caption for figures but also captions for the
R code. There is no easy standardized way to use code listings with
captions and to evaluate the code at the same time, but I [found a
workaround](https://github.com/quarto-dev/quarto-cli/issues/1580#issuecomment-1552673825)
with the following structure of code options in the code chunk:
```
#| label: fig-name
#| fig-cap: "fig-title"
#| attr-source: '#lst-fig-name lst-cap="list-title"'
```
This code generates a warning because at the moment the `=` symbol is
not allowed in RStudio when running a R chunks interactively in a Quarto
document. [See issue
13326](https://github.com/rstudio/rstudio/issues/13326). Although I got
a warning the code does what I want: It gives the figure and the code
listing a heading and evaluates the code at the same time.
## Glossary
I started a glossary using the
{[**glossary**](https://cran.r-project.org/web/packages/glossary/index.html)}
package by Lisa DeBruine [@glossary]. A glossary entry is visualized
with a double underline. Every chapter has a section where the text of
all glossary entries of the chapter are displayed. When you hover with
the mouse over the link it opens a pop-up window with the glossary text.
You can see example in the section about my motivation for this ebook
(See @sec-book-motivation).
I am using this glossary for all my other Quarto books but it is till
work in progress. Please keep in mind that I collected the definition at
various places and be attentive because there is no guarantee that the
entry is appropriate and correct. I have added the sources where I got
the content for the glossary entry.
## Session Info
Every chapter ends with a session information printed with the
`sessionInfo()` function.
::: callout-warning
###### Warning
I wrote this book as a text for others to read because that forces me to
be become explicit and explain all my learning outcomes more carefully.
Please keep in mind that this text is not written by an expert but by a
learner. In spite of replicating most of the content it may contain many
mistakes. All these misapprehensions and errors are my responsibility.
In any case I am the only responsible person for this text, especially
if I have used code from the resources wrongly or misunderstood a quoted
text passage.
:::