/sci/ - Science & Math

this is my secret hangout go away /hoc/

Determine the union set <span class="math"> \cup {{a,b},{c}} [/spoiler]

I do not understand what the function is, and it's not in the textbook. And googling doesn't work because I just get a million results talking about the simple definition of union...

Halp?

I don't want the answer, just if someone knows what the "set union" is, please lmk.

<span class="math">>>>/b/[/spoiler]

<span class="math">>>5108844[/spoiler]

<span class="math"> \uwotm8? [/spoiler]

<span class="math"> \u woy m8? [/spoiler]

anyone have any good books or resources with problems and solutions for a semi-advanced matrix algebra, preferably for statistics?

The book we're using is "Advanced Calculus with Applications in Statistics", and although the matrix algebra section is quite difficult, it's not very long.

>tfw the amount of people taking stats decreases quicker than <span class="math">e^{-x^2}[/spoiler] at <span class="math"> x > 0 [/spoiler]

>linear
>regression
>analysis

pick three

regression analysis

regression analysis

it's a differential equation, more specifically it's a boundary problem.

why you are calling it cauchy's problem i am not sure.

here's a hint: use an integrating factor

>freshman undergrad here
>overly ambitious faggot
>graduate degree

lol

go fuck yourself

Doing a (pure) regression analysis course.

Already did my econometrics so I know what it's about, but what kind of pre-req material from mathematical statistics is most important?

I'm going to be honest, I did it in summer school a couple years ago and I was kind of shitty at deriving probability distributions and shit like that.... (chapter 8-10 out of wackerly's book is where I started to not give a fuck)

using montgomery's intro to regression modelling book....

I hate this "experiment" with a passion. Maybe i'm just ignorant.

But I think it's fucking stupid.

Is it supposed to be an analogy for something in QM? Like flatland for discussing dimensions or something?

Either way it's pure shit.

>>5022162

So does this mean that the set {1,{1},{{1}},{{{1}}}} has 4 elements as well?

And if so, are the elements in the set equal? If we're referring to |R then aren't all the elements in the set corresponding to the exact same thing?

Economics guy here.

This isn't even econometrics, it's just a review of probability. I suggest using statistics notes/textbook.

1. Use the z-table.
2. look up formulas for the SD and Var. (they are related)
c, d, e,f: just use the expected value and variance laws. Don't let this question intimidate you. it's probably the easiest question on the whole assignment.

3. you're going to need to "normalize" these distributions. Look it up. Once normalized, just use the z-table.

>>5022131

But did you weigh 1000 pounds right before hitting the scale? No, you were the same. But you had 1000 pounds of force....

>>5022124

Like, if you dropped a 10 pound steel ball off a building and froze time half way down, then somehow weighed it. Would it actually weigh more? I think the mass would be the same but it would still measure out heavier because our weighing methods actually do allow for force.

Jump on a scale, it will shoot up to say, 1000 pounds, before going back to your regular weight.

Are these examples of what you're asking?

Do you even get heavier? Or do you just have a large force?

Haha, I wear different shoe sizes with different shoes manufacturers! Jokes on you, ohpee.

>It's just one proof after another, right?

Yeah, basically. What book are you using?

>>5022091

Something tells me there's a lot more to it than this picture.

>>5022079

Is it intuitive why objects are attracted to each other? Since the universe is expanding it would seem like things would just be moving apart.

Is ti the mass, and only the mass, that causes the attraction? Does mass have a non-intutivie property that causes attraction?

>>5022072

Thanks, tips. But what I said though still isn't incorrect, (unless I should replace dense with massive).. Since the more massive object will "win" the battle. Right?