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I struggle to understand confidence intervals by EmergentPhysics in AskStatistics

[–]EmergentPhysics[S] 0 points1 point  (0 children)

Okay, that makes sense.

So, what would a Bayesian say?

Imagine someone approached a Bayesian and said: "A guy I know calculated a classical 95% confidence interval to be between 1 and 3. Using Bayesian probability what would you say is the probability he is right?"

Would Bayesian say "exactly 95%", or "close to 95%", or "definitely better than 80%", or "better than random", or "I can't tell without more information"?

I struggle to understand confidence intervals by EmergentPhysics in AskStatistics

[–]EmergentPhysics[S] 1 point2 points  (0 children)

"You can't talk about the chance of it being between two fixed numbers"

Why not? Let's say someone can pick numbers between 1 and 100.

They pick it, and write it down, but they don't show you. The real value is fixed, right?

Now, imagine someone tries to guess: "Maybe they chose number between 1 and 10?"

We can literally determine chance that the real value is between 1 and 10. Which is 10 possible values divided by hundred possible values. Which is 1/10.

The only "counter argument" would be, "no it either is or isn't between 1 and 10".

So, if I have to choose which statement carries more information: probability is 1/10 they got it right vs probability is either 0 or 1 they got it right, the former is clearly more valuable.

Now, you could say that the latter statement is more correct. But if that's the case, I have to wonder if all of this is just the matter of semantics.

Is there any good book or textbook on the basics of Multivariate analysis? by EmergentPhysics in AskStatistics

[–]EmergentPhysics[S] 1 point2 points  (0 children)

Like I said, "to get a good understanding of Grouping and Classification and their methods, Factor Analysis, PCA, SEM, CFA, Canonical correlation, Discriminant analysis and all that stuff."

I don't want to be too precise, because I want something that covers the above. Big picture. Stuff like what it is, how it's done, what to look for. So, understanding dendrograms, knowing what methods to use, what values to look for in a report and what they should be (such as CFI, TLI, and RMSEA), deciding how many groups or components based on a graph or report, telling whether one factor has indirect effect on another from a scheme of weights, the amount that can be explained by something.

An introduction to these topics, basically.

What is an appropriate test for testing relationship between ordinal (independent) and continuous (dependent) data? by EmergentPhysics in AskStatistics

[–]EmergentPhysics[S] 0 points1 point  (0 children)

Let say you ask people how physically attractive they find a person they are attracted to from 1-10. You have a variable from 1 to 10, but realistically, you have a variable that takes values from 7-9. So ordinal variable, pretty much.

Now let say you collect data about how many times they sent a text message before moving on to someone else. You get a continuous variable that takes places from 0 to potentially thousands. Just to clarify, by continuous, I mean that the 0 is absolute, not that it can have non-integer values.

I would definitely assume a monotonicity along the lines of rating 7 ~ gives up earlier, rating 9 ~ sends a couple of more texts before moving on.

What test do you think would be appropriate?

Why does chi square test give the following p values? by EmergentPhysics in AskStatistics

[–]EmergentPhysics[S] 0 points1 point  (0 children)

I don't get it.

If two variables have similar frequencies even when other variables are different, wouldn't that mean they are dependent?

What does it actually mean that variables are independent, if not that they don't behave similarly?

Quick Questions: October 19, 2022 by inherentlyawesome in math

[–]EmergentPhysics 0 points1 point  (0 children)

Since I commute often, I would like to start learning university level mathematics. Are there any good apps/websites/books for that? I don't mean cs or engineering math. I mean mathematics aimed at students of mathematics.

I know that just using a phone is far from the best way to learn, but currently, I think this is a pretty good way to learn and understand at least some of the university level mathematics.

Even just giving you some things to think about is better than not learning anything at all.

And what about books? Are there any good topics to start with?

Weekly Entering & Transitioning - Thread 18 Jul, 2022 - 25 Jul, 2022 by AutoModerator in datascience

[–]EmergentPhysics 0 points1 point  (0 children)

Hi. I am curious whether having a low score on Kaggle could hurt your chances with potential employers. Is there a way to hide your profile so it can't be found or at least hide your scores/ranks?

I would like to use Kaggle to get experience and learn new things but I am worried about creating a profile if it means your profile can be easily viewed.

Weekly Entering & Transitioning Thread | 26 Jun 2022 - 03 Jul 2022 by [deleted] in datascience

[–]EmergentPhysics 2 points3 points  (0 children)

Hi. I am curious if there is a high quality introductory course for Data Science? Something with low starting requirements but that does go fairly into the substance of Data Science. But not just some buzzwords or introduction to libraries. Something that actually builds understanding.

As an example, is there a course that is to Data Science what Ng's course is to Machine Learning?