Reddit mentions of The Cartoon Guide to Statistics

For "books written for kids", I was a child prodigy and I liked the cartoon guides - I read the stats and the physics ones. I liked the how did we find out series as well, I think?


Textbooks might not be so bad. You find them dry, but he might not.


Emailing professors in the area was very helpful. If he understands what he's learned from the differential and integral calculus textbook, he's probably ready to talk to professors.


You don't necessarily need to teach him to follow in anyone's footsteps. If he's reading textbooks for fun, he's probably enjoys doing that. It's more important that he keep doing what he enjoys than that he imitates someone else who was successful. Still, it's nice to know about people who were similar to you in history! But it's not like he needs to go into physics or math to take advantage of his genius - some former child prodigies are already working in those fields, and while I like to think most are doing good work and advancing the state of their fields, none of them have revolutionized them recently.

You might need this book

95% confidence with a margin of error of ±5% for a population of 25,000,000 you would need about 385 people. The real problem here is how biased is that sample. By that I mean, do they have a statistically representative collection of people?

I've never read it myself, but I've heard quite good things about this book: https://www.amazon.com/Cartoon-Guide-Statistics-Larry-Gonick/dp/0062731025

At my old job, we used to keep it on our team's bookshelf, along with a bunch of very dry graduate texts in statistics.

Heya!

First things first, it's going to be ok! Lots of people enter sociology PhD programs with no background in sociology (or even a related social science!) at all. So, having majored in Sociology means you should have a much better lay of the land than some of your peers. That said, your classes will likely assume very little specific knowledge of sociology. For better or for worse, Sociology in undergrad is not treated as a "cumulative" subject where students are expected to master material in one class and then apply it in another. Grad school will expect that of you, to some extent, but it will not assume you start with much.

Second, if you are specifically worried about stats, I'd highly recommend reading some very light introductions that familiarize you with the concepts and ideas. Don't spend a lot of time with specific formulas, derivations, or software - your graduate stats sequence will cover all of that, again assuming you know basically nothing to start with. Instead, try to get a feel for statistical arguments, and for the basic ideas of probability, distributions, sampling, and so on. Start with something like The Cartoon Guide to Statistics. Then, read some quantitative sociology. Check out ASR or AJS or other big journals in the field. Find some articles on the topics that interest you and try to read through them to get a sense of how they employ quantitative methods. Don't expect to understand everything, but see what you can piece together.

Beyond that, I'd highly recommend checking out Fabio Rojas's guide Grad School Rulz (most of the content is available as a set of free blog posts on OrgTheory). I don't agree with absolutely everything Fabio says, but his advice is generally solid, and he covers all the important topics. Even if you don't take all his advice, reading the book will help you figure out what sorts of questions you should be asking and thinking about.

If you have any other specific concerns, let me know and I'm happy to give more targeted advice! Beyond that, good luck, and welcome to Sociology!

For a novice who is looking primarily to understand statistics rather than perform statistical analysis, I would consider The Cartoon Guide to Statistics. It is intended for total beginners and the medium makes the content a lot less dry than most statistics books.

http://www.amazon.com/Cartoon-Guide-Statistics-Larry-Gonick/dp/0062731025/ref=sr_1_1?ie=UTF8&qid=1310245777&sr=8-1

There is some quality in this book!

vllt zu grundlegend für dich, das hier fand ich ganz gut:

https://www.amazon.de/Cartoon-Guide-Statistics/dp/0062731025

https://www.amazon.com/Cartoon-Guide-Statistics-Larry-Gonick/dp/0062731025

If your just looking for a concept overview the cartoon guide to statistics is great. It's easy to read and filled with great visuals and examples.

If you want to learn how to do intro statistics/practice, look no further than khan Academy.

Honestly, ignore the "for engineering" part of "Statistics for Engineering." They're largely the same content.

How much calculus have you taken? Does the class use calculus?

First, the cartoon guide to statistics is surprisingly helpful for some people.

For a more traditional textbook, you might try Devore's main intro book.

Almost every student finds statistics confusing and it's either difficult to teach, or just difficult to learn. It's also a fractal discipline, since you can keep going deeper and deeper, but it's generally just going over the same few concepts with additional depth. If you end up in a class that's not well suited to your mathematical background it's especially frustrating.

Good luck.

It sounds like your questions are mostly statistics based. This book is a good intro - not too intimidating.
http://www.amazon.com/Cartoon-Guide-Statistics-Larry-Gonick/dp/0062731025

This will sound wimpy, but The Cartoon Guide To Statistics is pretty good, as in awesome for concepts. I'd recommend it as a supplement to whatever textbook you choose.

Totally depends on your stat background. If it's minimal id do khan Academy. This is a good into book http://www.amazon.com/gp/aw/d/0062731025/ref=redir_mdp_mobile/192-3922040-7644940

What's your background?

Not exactly an answer to your question, but I found the book, The Cartoon Guide to Statistics (authored by one of my Temple Statistics Professors, Woollcott Smith), to be both helpful and entertaining.

https://www.amazon.com/Cartoon-Guide-Statistics-Larry-Gonick/dp/0062731025

As far as "best" I can't say. It also depends on what in statistics you want to learn, but I agree with /u/solkim that probability and stats go hand in hand and if you want a good grounding in statistics you will also need a good grounding in probability. Having said all of this, and as silly as it may sound, the Cartoon Guide to Statistics is actually quite good at helping to understand and learn statistics (and probability) concepts.

From another discussion (http://www.reddit.com/r/statistics/comments/2mqyn5/where_to_learn_statistics/):

http://www.amazon.com/Cartoon-Guide-Statistics-Larry-Gonick/dp/0062731025/ref=sr_1_1?s=books&ie=UTF8&qid=1416393382&sr=1-1&keywords=cartoon+guide+to+statistics

I'm doing the same. Here are a couple of resources that you may find helpful.

• Book: Cartoon Guide to Statistics (better than it sounds)
  
• OCW: Statistical Thinking for Managerial Decisions
  
• OCW: Introduction to Probability and Statistics
  
  That should be enough to get you going. Good luck!

Cartoon Guide to Statistics

Surprisingly effective intro to probability

might be too informal for your purposes though...

Ugh, this should not be a pie chart. uh...here.

>A steep learning curve is one where you gain proficiency over a short number of trials. That means the curve is steep.

Congratulations, you've lost all credibility as an analyst by using a technical term to mean the exact opposite of what you were trying to say. Learn the technical jargon before you fuck up mean and median in front of your boss. A Cartoon Guide to Statistics does an amazing job of explaining most of the terms and formulas. If you don't want the book, watch Khan Academy's Statistics Course on YouTube.


Next, if you have Microsoft Excel, enable the Solver and Analysis ToolPak. This will allow you to perform all of the analyses performed in the book/videos. OpenOffice has a similar toolpak.

As long as you know how to perform an ANOVA or solve for a p variance, everything else should be industry specific models/applications and no one will realistically expect for you to know how that company's particular processes work.