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  • 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
  • Is there a good browser viewer to see an R dataset (. rda file)
    Here are a few basic options, but like you, I can't say that I'm entirely happy with my current system Avoid using the viewer: I e , Use the command line tools to browse the data head and tail for showing initial and final rows str for an overview of variable types dplyr::glimpse() for an overview of variable types of all columns basic extraction tools like [,1:5] to show the first five
  • Correlation and standard deviation - Cross Validated
    The formula for the correlation is equal to the covariance between x and y, divided by the standard deviations of x and y So what happens if you keep on denominator (where the standard deviation is) larger and large?
  • hypothesis testing - Choosing between a MANOVA and a series of t-tests . . .
    Whereas, the t test is appropriate test of difference between the means of two groups at a time (e g , boys and girls) It is also possible to compute a series of t tests, one for each pair of means




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