Bayesian Probability for Babies

Baby University

by Chris Ferrie

Fans of Chris Ferrie's Rocket Science for Babies , Astrophysics for Babies , and 8 Little Planets will love this introduction to the basic principles of probability for babies and toddlers! Help your future genius become the smartest baby in the room! It only takes a small spark to ignite a child's mind. If you took a bite out of a cookie and that bite has no candy in it, what is the probability that bite came from a candy cookie or a cookie with no candy? You and baby will find out the probability and discover it through different types of distribution. Yet another Baby University board book full of simple explanations of complex ideas written by an expert for your future genius! If you're looking for baby math books, probability for kids, or more Baby University board books to surprise your little one, look no further! Bayesian Probability for Babies offers fun early learning for your little scientist!

Genres: Mathematics, Picture Books, Childrens, Science, Nonfiction, Stem

24 pages, Board Book

Published July 2, 2019

About the author

I am Chris Ferrie, father of four and happy husband. My day job is academic research where I follow my curiosity through the word of quantum physics. My passion for communicating science has led from the most esoteric topics of mathematical physics to more recently writing children’s books.

Reviews

[Manybooks · Rating 1 out of 5]

No indeed, my one star rating for Chris Ferrie's 2019 Bayesian Probability for Babies does not really have anything to do with the book heading claiming that this is a board book supposedly meant for actual infants even though Ferrie's text and accompanying artwork combination for Bayesian Probability for Babies (and indeed for all of his Baby University series of board books) are at least in my humble opinion much more suitable for young children from about the age of two to five and maybe even beyond that (as while I do tend to find Chris Ferrie's Baby University titles a trifle annoying, misleading and also as such majorly gimmicky, this does not really ever affect my reviews/ratings per se, although I do increasingly wish that different and not baby-oriented book headings could be used, that the titles certainly do not equal the textual and illustrative contents Ferrie and his respective co-authors provide and demonstrate).

But indeed and also sadly, frustratingly, my one star ranking for Bayesian Probability for Babies totally and indeed pretty much ONLY has to do with the fact that I myself have been having major, have been having huge issues and problems even somewhat, even remotely understanding and figuring out Chris Ferrie's words and his probability, his mathematical explanations in Bayesian Probability for Babies (both textually and I must say visually as well, since the accompanying artwork is for my aesthetic tastes ugly, bland and neither successfully mirrors nor adequately explains the featured writing and in fact kind of makes Chris Ferrie's presented words even more potentially confusing to me). And yes, my frustration with the lack of comprehensibility regarding Bayesian Probability for Babies has been especially pronounced and problematic with the mathematical formulae Ferrie features and uses as part of Bayesian Probability for Babies (which are in my opinion NOT simple and actually kind of majorly and infuriatingly remind me of the kind of befuddling and insufficiently explained crap and garbage I got for mathematics and for probability/statistics during high school and which made me and continues to make me often totally and utterly despise and loathe anything even remotely mathematically based in scope). So I guess, I might perhaps even be the wrong type of person to review Bayesian Probability for Babies (totally not math inclined and also not at all at ease with the subject). But honestly and on the other hand, since Chris Ferrie has repeatedly stated that he believes STEM is taught the wrong way at the school (at all levels of school) and that we should be starting STEM thematics early and also with very young children (and which is why he supposedly created the Baby University board books in the first place), frankly, since it would generally be parents, early childhood educators etc. who would be using Bayesian Probability with the intended audience of two to five year olds, if I as an adult who has never been very good at maths have so much trouble with the probability themed contents of Bayesian Probability for Babies, then what is being featured by Ferrie and how this is being shown both verbally and equally visually by him is pretty much a huge failure and as such not to be recommended as suitable for young children.

For come on, most young children are not budding math geniuses (like TVs Sheldon Cooper), and I do certainly know that when I was a toddler, I would neither have understood nor in any way enjoyed Bayesian Probability for Babies, that Bayesian Probability for Babies is also one of the Baby University board books that would certainly benefit from having a section included explaining the basics of bayesian probability for parents/caregivers and maybe even how to approach this with very young children (in particular for those of us not adept and naturally talented regarding mathematics), and that I was actually hoping Chris Ferrie would be able to explain bayesian probability simply and in an easy to understand manner for and to me, but that pretty well everything with Bayesian Probability for Babies has left me hugely and sadly disappointed.

[Lata · Rating 4 out of 5]

A much clearer explanation of probability than any I received in college or university.

[briz · Rating 4 out of 5]

Again, who is the audience of this cynical, gag series of baby university books?! Not interesting for babies. Not funny enough for parents, beyond the first-impact "heh" when you see the title. Enough! I banish these from baby registries everywhere. These are like those "World's Okayest Boss" mugs, but even those are better, because (a) a mug is functional, and (b) those are funny.

Four stars because I do love Bayes.

[Hugh Butler · Rating 1 out of 5]

catchy title. completely false. from the words "bayesian probability" to its conclusion this tiny book renders a complex and grand mathematical/statistical axiom to a bite from cookies!

no baby should be subjected to this. or most adults. including me.

[Yasmin M. · Rating 5 out of 5]

Well I am getting gifts for a baby shower and I decided to look at this series. I must say as a scientist I was skeptical (yeah I know how that sounds but it is the only cool thing I can say about myself so give me a break 😆 ), I mean how can you simplify that for babies?
This was pretty good I must say.
Bayesian probability is probably the basis of all the analyses worth reading these days.

[Michelle Pan · Rating 5 out of 5]

Fire.

[Sara · Rating 3 out of 5]

حس میکنم برا گروه سنی خودش زیادی بزرگونه نوشته شده بود.

[Tanya · Rating 4 out of 5]

I had this read to me as a video - wow, what a board book. I actually want to look for others in the series by this author.

[Christina · Rating 2 out of 5]

Want to learn about Bayesian probability as a baby well this book attempts to explain it but I was left still with some questions and no real understanding of this concept despite not being a baby. My baby listened to me read it but lost interest as the pictures were not very engaging and despite my enthusiastic voice the content was a bit boring and left me only with a desire to eat cookies.

[ana carolina · Rating 1 out of 5]

how is it even possible for the final result to be 3/4? doesn’t make any sense
you have NINE 𝐜𝐚𝐧𝐝𝐲 cookies (the ones with the balls) and ONE 𝐧𝐨-𝐜𝐚𝐧𝐝𝐲 cookie (without any balls), equaling TEN COOKIES.
the probability of a no-candy bite on a candy cookie is 1/3.
the probability of a no-candy bite on a no-candy cookie is 3/3 = 1.
if you have TEN cookies (as described above [9 candy cookies; 1 no-candy cookie]), and take a bite of each, we’ll have:
4 no-candy bites (1 no candy bite from the no-candy cookie + 1/3 of the bites from the 9 candy cookies = 3 bites) and 6 candy bites (all from candy cookies).
then it says:
“1/3 of the candy cookies (9 in total) have a no candy bite”, which makes us with three candy cookies with no-candy bites.
and then comes the conclusion that doesn’t make any sense:
“the probability of a candy cookie with a no candy bite is 3/4”. and not only that, it illustrates the “4” 𝐜𝐚𝐧𝐝𝐲 cookies with an image of three candy cookies AND a 𝐧𝐨-𝐜𝐚𝐧𝐝𝐲 cookie. so that’s not 4 candy-cookies, but three candy cookies and one no-candy cookie.
oh my god

[Betsy · Rating 3 out of 5]

This book could be improved by dividing the cookie evenly into thirds instead of having the cute bite marks. On the pages where they say the probability of a no-candy bite given a candy cookie is 1/3, there's a whole fourth center piece with a candy right on the edge. Intuitively, I would guess that the probability of a no-candy bite given a candy cookie is 1/4. Yes the center piece doesn't follow the shape of what a bite is, but in that case, the bigger crime is that there is a whole section of cookie that is uneaten and has two whole candy bits in it!

[Writer · Rating 3 out of 5]

Bayesian rule is likelihood times prior, then divided by probability of data

3/4 is probability of candy cookie conditional on data of bite of cookie.

Proof:

Likelihood is 1 out of 3 bitten cookies would be candy cookies.

Prior is probability of C or candy cookie, and it’s 9 out of 10 cookies.

1/3 * .9 is .3

The probability of the data or the bitten cookie is 4 out of 10.

When .3 is divided by .4, it’s 3/4 for the probability of getting a candy cookie given a bitten cookie.

[Ezel · Rating 2 out of 5]

Trying to get a decent conception of Bayesian Probability as I barely have any knowledge about it, this book makes it a bit more clear for those with barely any exposure to Bayesian Probability, by that I mean it lives up to its title. I will have to read it a couple more times and engage in actual lectures to get a grasp over the concept as a whole. Baby Steps !

[Anh Nch · Rating 4 out of 5]

4 stars instead of 3 because I read this book in 2 minutes, yet it pushed me to go down a rabbit hole of 1 hour trying to understand different examples and implications of Bayesian probability on Youtube. And I had no regret.

[Johannes · Rating 2 out of 5]

Obviously not to be taken seriously, but still makes a serious attempt (and sort of fails) at providing a simple explanation of Bayesian Probability. Not a great idea to use cookies as the example. Could have been either a lot funnier or a lot more useful.

[Al Adducci · Rating 5 out of 5]

What are odds I would find this book?

[John Kaye · Rating 4 out of 5]

review to come later. Probably needs thought.

[TJ & AJ · Rating 3 out of 5]

Well, it's more engaging than the other Ferrie book we have.

[L. Luck · Rating 4 out of 5]

Better than my Bayesian stats class and with far less programming!

[Pinky · Rating 4 out of 5]

Baby can learn about probability, prior distribution, posterior distribution, and more in this book.

[Sarah Corsi · Rating 3 out of 5]

Fun!
Entertaining for all ages.
I am still none the wiser about Bayesian Probability.

[Nadege Dupont · Rating 3 out of 5]

Definitely not for babies. ;-)

[Josephine Bivins · Rating 4 out of 5]

I like the topic, my Mommy is still trying to understand

[Lena Lee · Rating 3 out of 5]

A bit meh 😕

[Reading With Dad · Rating 5 out of 5]

Watch a readaloud of
Bayesian Probability for Babies
https://www.tiktok.com/t/ZTFU8wV7s/

[Amanda · Rating 3 out of 5]

Just read the other reviews.

[shawty · Rating 1 out of 5]

As someone well versed in probability compared to the average 6 month old, this stumped me

[Corey · Rating 1 out of 5]

This is an adult level explanation of probability with a food metaphor. This is for babies. I read it. I'm an adult. I didn't understand it. I don't think babies can.

[Always Have a Book · Rating 4 out of 5]

Where were books like this when I was on high school?

[K Morlando · Rating 5 out of 5]

We loved reading this!