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How to resolve the ambiguity in the Boy or Girl paradox? 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)
Hypothesis testing: Fishers exact test and Binomial test The result obtained with the Fisher's exact test ("no significant difference between the proportion of girls and boys who finds that the cake tastes good") seems to contradict the results in (1) and (2), which say that the "more than 50% of the population of girls find that the cake tastes good" (1), and "no more than 50% of boys find that the
probability - What is the expected number of children until having the . . . You can consider starting from position 1 for the difference of boys girls and move up and down randomly with 50% probability until reaching zero These type of walks have been described here: What is the distribution of time's to ruin in the gambler's ruin problem (random walk)? and based on the results in those answers we can see that the
Why is gender typically coded 0 1 rather than 1 2, for example? $\begingroup$ Using a 0 1 coding scheme is essentially useful when applying regression models among others, although several coding schemes are possible, e g -1 1 (but it will change the interpretation of the regression coefficients)
Interpretation of regression coefficients with multiple categorical . . . It's the difference between the (predicted) mean of girls in girls-only schools and the (predicted) mean of girls in mixed schools You can see this by looking at the design matrix or solving for a predicted value using the fitted regression equation Let's make some simple data and work through this
ANOVA vs. T-test for two groups - Cross Validated Stack Exchange Network Stack Exchange network consists of 183 Q A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers
should I use log or raw data in non parametric tests? If you only compare girls vs boys, Kruskall-Wallis test and Wilcoxon test should be equivalent But anyway, as for the Wilcoxon test, the Kruskall-Wallis test is not affected by log-transform, as explained by stats_model $\endgroup$ –