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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
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
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 Shapiro-Wilk test - Cross Validated Considering that you are pretty new to statistics, I suspect that you are thinking about this because these are residuals of an estimate of a mean and you want to know whether the assumption of normality is valid for confidence estimates using a t t -distribution t t -tests are quite robust to violations of this assumption, the data look vaguely normal in Henry's q-q plot, and the Shapiro
What does 1x1 convolution mean in a neural network? I am currently doing the Udacity Deep Learning Tutorial In Lesson 3, they talk about a 1x1 convolution This 1x1 convolution is used in Google Inception Module I'm having trouble understanding wh
Trying to understand the fitted vs residual plot? [duplicate] A good residual vs fitted plot has three characteristics: The residuals "bounce randomly" around the 0 line This suggests that the assumption that the relationship is linear is reasonable The res