Open kenjioman opened 5 years ago
Section 4.4.1.3, p.95
Section 4.4.3, p.99
Section 4.3.2, p.83
Section 4.4.1, p.95-96
Side comment: "probability of the data" doesn't seem like the best way of expressing this. The probability of observing a given sample on a continuous distribution is zero. As far as I recall there is no discussion in previous chapter of the simplification of saying "probability of the data".
Hi Richard,
I am following Pablo’s lead and posting typos in hopes that they are helpful.
-Sean
AUGUST 2 VERSION
P130 - "here I’ve chosen R for marriage rate" --> "here I’ve chosen M for marriage rate"
P211 - "In previous chapters, when I forced us to revise the priors until the prior predictive distribution produced only reasonable outcomes. " --> Delete "when"?
P218 - "To see how the WAIC calculations actually work, consider a simple regression fit with map:" --> "map"--"quap"
n <- length(waic_m6.6) --> waic_m6.6 is not defined, so I think this should be n <- length(waic_m6.7)
234 - mentions the 'ensemble' function, but I do not this it has been used in the chapter.
270 - the chain very slow makes -- the chain very slowly makes
287 - the chains is much clear, --> the chains is much clearer,
SWITCHED TO READING THE SEPT 24 VERSION
P326 The problem is that deviance is part normalizing constant. Missing word?
P338 - "You can reproduce is with this code:" is -> it
P418 - "The values α ̄ = 1.4 ..." 1.4->1.5
P419 - "Now to fit the model to the simulated data, using map2stan [Ulam]. I’ll use a single long chain in this example, but keep in mind that you need to use multiple chains to check convergence to the right posterior distribution. In this case, it’s safe. But don’t get cocky." Needs editing because the code example uses 4 chains
P425 - "I’ve down this on" --> down -> done
P434 - "the same simulate chimpanzee," simulate->simulated
Dr. Sean S. Downey Associate Professor, Department of Anthropology Core Faculty, Sustainability Institute The Ohio State University 4034 Smith Laboratory 174 W. 18th Avenue Columbus OH, 43210-1106
Office: 614-688-3904 Mobile: 240-392-0220 Belize: +501-664-9012 SkypeId: seandowney1234 https://osu-cfaes.zoom.us/j/3613727623
On 29Oct, 2019, at 10:42 AM, PabloIsCoding notifications@github.com<mailto:notifications@github.com> wrote:
Section 4.4.1, p.95-96
Side comment: "probability of the data" doesn't seem like the best way of expressing this. The probability of observing a given sample on a continuous distribution is zero. As far as I recall there is no discussion in previous chapter of the simplification of saying "probability of the data".
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Hi @downey205 , I noticed that you answered an email so you may not have noticed that there are open issues on github for each chapter of the book. As a matter of fact I didn't start this thread!
I have no idea if Richard cares about where we post the typos, but maybe some of yours were already spotted in some other thread (I haven't checked though). I'd suggest that you take a look here: https://github.com/rmcelreath/statrethinking_winter2019/issues
By the way, it's a great idea to post the date of download of the book just in case they change, so I'll start doing it myself!
(Still present as of the 2019.02.19 version)
Section 4.1, Pg 72, last sentence of 1st paragraph of section
who
are standing ...who
.who
makes this sound better, in my opinion).the
proportion of the thousand people who are standing ...".Section 4.3.5, Pg 88, Model definition equations (between code block 4.26 and 4.27)
178, 20
), but the R code on the right saysmu ~ dnorm(
156, 10)
178, 20
Section 4.4, Pg 92, Rethinking "What is regression"? box, 2nd paragraph
Section 4.4.1.3, Pg 96, 1st full paragraph on page
??
Defining $\beta$ as ...Section 4.4.3.4, Pg 106, paragraph after code block 4.55, last sentence
right-hand plot
in Figure 4.7.right-hand
plots in Figure 4.7, but the consequence of the amount of $\mu$ depending on the weight is observable in any of these plots.Section 4.5.1, Pg 113 or 114, code block 4.69 or the model specification (math) right above it
1
), but the code block uses Normal(0,10
).