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Use standard type for greek letters, subscripts and superscripts that function as identifiers (i.e., are not variables, as in the subscript “girls” in the example that follows), and abbreviations that are not variables (e.g., log, glm, wls) Use bold type for symbols for vectors and matrices Use italic type for all other statistical symbols. 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.
1st 2nd boy girl boy seen boy boy boy seen girl boy the net effect is that even if i don't know which one is definitely a boy, the other child can only be a girl or a boy and that is always and only a 1/2 probability (ignoring any biological weighting that girls may represent 51% of births or whatever the reality is). Expected girls from one couple$ {}=0.5\cdot1 + 0.25\cdot1 =0.75$ expected boys from one couple$ {}=0.25\cdot1 + 0.25\cdot2 =0.75$ 1 as i said this works for any reasonable rule that could exist in the real world An unreasonable rule would be one in which the expected children per couple was infinite. A couple decides to keep having children until they have the same number of boys and girls, and then stop
Usually, we use anova if there are more than two groups But you also can use anova with two groups, as you describe In that case anova will result in the same conclusion as an student's t test, where A couple decides to keep having children until they have at least one boy and at least one girl, and then stop
Assume they never have twi. Assume that x x is a random height of a boy and y y is a random height of a girl and these variables are independent Now, the probability you want to assess is
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