Specifically in the statistics arena. It has been a long, long time since I had to do anything with Expected Value and Variance and I've got a problem that requires that knowledge. I just need to get some direction in how to head with it.
Is anyone here really good at math
- Thread starter kc78
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That is the focus of my applied math degree that I backed into. And I am probably no help whatsoever. Go over to the actuary boards (they exist) or hit up someone on campus.
I've got a version of Minitab and have some stats experience (specific to stuff I normally work on).
What's the question?
Not good at math, here. Really had to try hard to succeed. I did get an "A" in statistics in college, but for me, if I don't use it I lose it.
Also there's a physics forum with a section where people help with a lot of different math topics.
I can recite most of the statistics off the 1986 and 1987 Topps Baseball Cards. I think I'm your man.
I just need a bit of direction in what the math wants so I can write the program to solve this.
My initial thought was to create a vector with 100 values in sequential order, another vector with 100 values randomized, and to then just loop through it to see how many match since it just wants the initial observation. But since it asks about expected value and variance I'm assuming it needs something more and I'm a bit lost.
My initial thought was to create a vector with 100 values in sequential order, another vector with 100 values randomized, and to then just loop through it to see how many match since it just wants the initial observation. But since it asks about expected value and variance I'm assuming it needs something more and I'm a bit lost.
Got up through Calc II and Dif Eq in college, so I'm pretty much an expert in statistics as well.
Mean - average
Median - middle one
Mode - the most common
Let me know if you need anything more advanced than that.
Mean - average
Median - middle one
Mode - the most common
Let me know if you need anything more advanced than that.
In the initial disbursement, it is expected that 69 out 420 females will receive their diploma. If the expected number had been 70, then 350 women would be left without a degree after the first go-around.
sounds like a binomial distribution. mean = np
variance = np(1-p)
eta: google “example 7.17: the smith college diploma problem - SAS and R”
variance = np(1-p)
eta: google “example 7.17: the smith college diploma problem - SAS and R”
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I'm Indian so basically I am the winner of this thread unless there's a Korean amongst HORT.
This is for a class in R.
And I did see that problem, however that problem is asking a slightly different answer. It's asking how many rounds until everyone has the diploma. This one simply wants to know how many would have it after the first round. I can write a for loop to simulate that, but I'm not certain if it's asking for more.
Not that I'm aware of.
I eventually did the following but I don't know if it's correct.
1. Created a vector of 1-100 to simulate 100 students
2. Created a vector which randomized the values from the student vector to represent the scrambled diplomas.
3. Created a loop to compare them 1 to 1 and sum a variable anytime they matched.
From there I determined the probability of success by dividing the number who matched by the number of students.
I determined the probability of failure by subtracting the above from 1.
I then determined the mean by multiplying the number of students by probability.
And the variance by multiplying numstudents * probability * probability of failure
Whether that's the correct math, I don't know but that's the best my google-fu can determine.
This is what happens when you go to grad school in your mid-40s. Undergrad statistics was a long, long time ago. lol
Had I known this was "textbook" problems, I'd have passed.
I don't remember half the stuff in math/stats/physics classes I got A's in.
I believe this is an n! (factorial) problem.
You have 1 orientation all the students line up in, and n! (or (n-1)! or whatever) permutations the diplomas can be given out.
So, you simulate out of those permutations, the combined likelihoods of 1, 2, 3, ..... n students all getting their diplomas on the first handout.
There will be a different answer if you're computing the probability that 1 will get their diploma, vs what the question here is, the likely number that will. But I think you can simulate this with those combined/summed factorial calculations.
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