I invented CPO-STV, ranked pairs and one version of the Condorcet-Hare voting rule. I wrote the book Collective Decisions and Voting. I have a BA from Reed College and a Ph.D. from the University of Chicago. I was an Assistant Professor at Harvard, and a Senior Staff Economist at the President's Council of Economic advisers. I am now a Professor of Economics at Virginia Tech.
hi - I'm trying to calculate the p-value for the click-out-rate.
Quick review:
click out rate = number of clicks per session
penetration = 1 if a session had a click 0 otherwise
The average penetration rate is then based on a sequence of trials whose values are either 0 or 1 ===> So it has a binomial(N,p) distribution. N = number of trials and p = success rate.
But what if my statistic gives a payoff other than 1 in the event of a success? What if my random variable pays according to a rate lambda (poisson) in the event of a success?
example: [0 0 5 0 2 0 0 11 0 0 0 0 8] for [fail fail success fail success success fail fail fail fail success]
what distribution is this then? - this represents the number of clicks in sequence of sessions/trials
In the link provided, I don't know how to solve Q3 part c. I actually don't even know what the question is asking. I did solve the above questions because there were textbook examples but not for part c. Any help is appreciated.
A homework asked me to prove this equation:
for x> -1, (1+x)^n ≥ 1+nx, n ∈N
Well, I used induction:
(1+x)^1 ≥ 1+1*x (true)
Assume (1+x)^n ≥ 1+nx, n ∈N is true for n = k
Will be proven the equation is also true for n = k+1
(1+x)^k+1 = (1+x)(1+x)^k ≥ (1+x)(1+kx) = 1+(k+1)x+kx^2 ≥ 1+(k+1)x
The problem is... the first equation holds up for any x, not just x>-1, and all the way until the final equation there also has no criteria for x>-1; meaning I "proved" the equation for all x; which is totally absurd: take x=-3 and n any large odd number and it's obviously untrue. What did I do wrong?
Hello!
I've got this book out from the library ("Rent Unmasked: How to Save the Global Economy and Build a Sustainable Future"), and I'd really like to get my hands on digital copies of the following chapters (or the whole book). Was wondering if anyone had sources for these:
- Kris Feder: Economics from the Ground Up: Public Revenue and the Structure of Production
- Nicolaus Tideman: The Needed Moral Revolution
I'm not asking for pirated sources, just any digital sources at all.
Thanks for any help!
The question I'm confused by is this: https://imgur.com/PgSj0SU
The answer (value of h) to the question in the official text book is 16.5ft. I keep getting an answer of h=12.8ft(approx) if i use the reference points in the image linked above. However, if I use my point 1 as the point at the top of the water in the piezometer, i get the correct answer.
When i get an answer of 12.8ft, I included the velocity head at point 1, which seems to be the reason i am getting the wrong answer, however, I don't see how including the velocity head is wrong.
I've linked an image of my workings here: https://imgur.com/3BBMT3I
(Please note i have converted everything to SI units. The bottom line is meant to say h = 3.91m which is approx 12.8ft)
I'd be grateful if anyone could explain to me the difference in answer when i use different reference points, as I thought my answer should always be the same regardless.
I understand Bernoulli's equation and the continuity equation in a basic capacity, but am getting caught on certain problems. If I was just to use them independently in their simplest problems, I probably wouldn't have an issue but I am with this for some reason and it's driving me bonkers. I'm getting particularly stressed at this as this is the paper that acts as a prerequisite to water engineering at my tertiary provider and what I most want to get into.
Some people that know me would say I live on stress when studying which is not healthy but I'm probably a bit too desperate to pass this paper which is probably holding me back from full understanding.
New to machine learning. Doing a bag-of-words style twitter sentiment analyses. Ran 10 fold cross validation, examined the best parameters for max_features as well as alpha value across all trials and chose the best ones for the test Data. Achieved 97% accuracy with training data. However when I submitted the test data for evaluation, this number was 68%. What am I doing incorrect? I thought the whole point of cross validation was to avoid over-fitting the data?
I’m currently in AP Physics 1, which does not teach fluid mechanics at all. However, I have been very curious about so I’ve learned about it via google. So, I just wanted to pose a certain scenario and ask a question about it: If a fluid flows threw a tube of area A1, and has a velocity of V1, if it suddenly encounters (still straight-ward motion) an area of A2 where A2<A1, why does the velocity still increase if the pressure would be higher at A2? My belief is that if a fluid is suddenly forced into a smaller area, it should undergo higher pressure and thus lower velocity, but why am I wrong?
tl;dr at bottom.
So I spent some time in excel because I was really just curious what some of these probabilities looked like. I originally just wanted to see the numbers for myself, but also though you guys might want to see them too.
I've seen some other posts about probabilities on here, but some are either answering different questions (I've seen coupon collector problem run on these probabilities a few times), but I wanted to see some cut offs.
For example, how many Red Star Orbs would I have to open to see a greater than 50% chance of seeing a 7 RS character (spoiler alert 366 days)? What about 33%? 25%? 10%? 5%? So I ran those numbers.
Then I wanted to see what the probability looks like for SPECIFIC character pulls. Then it spiraled out of control and I set the workbook up to look at pulling a character from the a Meta team. I looked at the difference between probabilities if you buy every RS offer in the store. I looked at the probabilities for 6 RS pulls and 5 RS pulls.
I was an econ major in my undergrad and it has been a hot minute since I did simulations like this, but I'm decently confident I'm at least CLOSE to what the right probabilities should be. Feel free to check it out and call me stupid. I definitely did a reallllly quick proof-read of everything, but there could still be careless mistakes. This wasn't meant to be a thesis in statistics or anything. If you aren't super familiar with math or probabilities, I'd tried to walk you through what I was doing (originally I was doing that for myself to make sure it made sense and I could follow what I was doing when I cam back to look at stuff later).
Additionally, I think Google Sheets does some earlier rounding than Excel, so if you are looking through the data and it doesn't match up with what I've listed, it is most likely a google sheets early rounding error. Shouldn't affect things TOO much. Also...this file is yuge. Might be easier to download it and check it out from there.
Anyway, here is the link:
https://drive.google.com/file/d/1FPlwq-gPCcDxoyFBjO8OxZ0wfWRIyThz/view?usp=sharing
Fixed the document, thanks u/AlArrache for catching my mistake.
TL;DR - I made a spreadsheet of a bunch of different probabilities for RS pulls. If you want a SPECIFIC 7 RS character and you are F2P, you will have a greater than 50% shot in about 80 years based on probability alone. And whales, if you buy the 6 Red Stars every day, you will have greater than 50% chance of pulling ANY NON SPECIFIC
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