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| mask_hypothesize <- new.env() | |
| ## This masks the infer::hypothesize function, and does one extra step of processing before returning the data | |
| ## The response variable is re-centered to have a mean equal to the hypothesized mean | |
| ## Normally the re-centering is postponed till the generate step, but since we're not using generate (it can't take a sample of arbitrary size from an empirical distribution) | |
| ## we've got to do it a little earlier! | |
| mask_hypothesize$hypothesize <- function(...) { | |
| x <- infer::hypothesise(...) | |
| response_var <- as.character(attr(x, "response")) | |
| mu <- attr(x, "params") | |
| x[[response_var]] <- x[[response_var]] - mean(x[[response_var]]) + mu | |
| return(x) | |
| } | |
| mask_hypothesize$hypothesise <- mask_hypothesize$hypothesize | |
| attach(mask_hypothesize, warn.conflicts = FALSE) | |
| rm(mask_hypothesize) | |
| ncbirths_pop <- readr::read_csv("https://bit.ly/ncbirths_pop") |> | |
| tidyr::drop_na(mage, gained, fage, weight) |
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