- How to resolve the ambiguity in the Boy or Girl paradox?
There's no paradox here, just ambiguity We're giving a vague description of a "real life" situation, and you're supposed to turn that into a well defined probability space in which to express events and their probabilities This is often hard or impossible to do, with the only possible conclusion being "some assumptions are missing" In this "boy and girl" problem, there is additional
- probability - What is the expected number of children until having the . . .
A couple decides to keep having children until they have the same number of boys and girls, and then stop Assume they never have twins, that the "trials" are independent with probability 1 2 of a boy, and that they are fertile enough to keep producing children indefinitely
- Hypothesis testing: Fishers exact test and Binomial test
Considering the population of girls with tastes disorders, I do a binomial test with number of success k = 7, number of trials n = 8, and probability of success p = 0 5, to test my null hypothesis H0 = "my cake tastes good for no more than 50% of the population of girls with taste disorders" In python I can run binomtest(7, 8, 0 5, alternative="greater") which gives the following result
- what is the difference between a two-sample t-test and a paired t-test
When you use a paired T-test, you are essentially doing a one-sample test, where your one sample consists of the paired differences between outcomes in two groups If you create a new sample of these difference values and then apply the formula for a one-sample T-test, you will see that this is equivalent to the paired test
- Ideal BandPass Filter - Signal Processing Stack Exchange
Let suppose x (t)= ∑ k=−∞∞ R(t − kT) ∑ k = − ∞ ∞ R (t − k T) R(t) = {1 0 [0, 2T] otherwise R (t) = {1 [0, 2 T] 0 otherwise x (t) is the input to an ideal bandpass filter with BandWidth = 1 (2T) BandWidth = 1 (2 T) and Center Frequency = L (T) Center Frequency = L (T) How can i find the output y (t) any help will be appreciated
- Why is gender typically coded 0 1 rather than 1 2, for example?
I think this question is best considered as two questions confounded The larger question is why use 0-1 coding rather than any other for an indicator or dummy variable The smaller question is why use 1 for male and 0 for female, to which one short answer is that many other codings are in use, including the opposite of 1 for female, etc , and also various complex codings allowing for unknown
- Building a linear model for a ratio vs. percentage?
Suppose I want to build a model to predict some kind of ratio or percentage For example, let's say I want to predict the number of boys vs girls who will attend a party, and features of the party
- Interpretation of regression coefficients with multiple categorical . . .
Cell "girls x boyonly school" is empty, likewise cell "boys x girlonly school" So I recommend you to obtain the vector of predicted values and check yourself, which differences the coefficients represent
|