Declare a null hypothesis about variables selected in specify().
Learn more in vignette("infer").
hypothesize(x, null, p = NULL, mu = NULL, med = NULL, sigma = NULL) hypothesise(x, null, p = NULL, mu = NULL, med = NULL, sigma = NULL)
| x | A data frame that can be coerced into a tibble. |
|---|---|
| null | The null hypothesis. Options include |
| p | The true proportion of successes (a number between 0 and 1). To be used with point null hypotheses when the specified response variable is categorical. |
| mu | The true mean (any numerical value). To be used with point null hypotheses when the specified response variable is continuous. |
| med | The true median (any numerical value). To be used with point null hypotheses when the specified response variable is continuous. |
| sigma | The true standard deviation (any numerical value). To be used with point null hypotheses. |
A tibble containing the response (and explanatory, if specified) variable data with parameter information stored as well.
# hypothesize independence of two variables gss %>% specify(college ~ partyid, success = "degree") %>% hypothesize(null = "independence")#> Response: college (factor) #> Explanatory: partyid (factor) #> Null Hypothesis: independence #> # A tibble: 500 x 2 #> college partyid #> <fct> <fct> #> 1 degree ind #> 2 no degree rep #> 3 degree ind #> 4 no degree ind #> 5 degree rep #> 6 no degree rep #> 7 no degree dem #> 8 degree ind #> 9 degree rep #> 10 no degree dem #> # … with 490 more rows# hypothesize a mean number of hours worked per week of 40 gss %>% specify(response = hours) %>% hypothesize(null = "point", mu = 40)#> Response: hours (numeric) #> Null Hypothesis: point #> # A tibble: 500 x 1 #> hours #> <dbl> #> 1 50 #> 2 31 #> 3 40 #> 4 40 #> 5 40 #> 6 53 #> 7 32 #> 8 20 #> 9 40 #> 10 40 #> # … with 490 more rows