ifr_os_prop_test
compares proportion in one group to a
specified population proportion.
ifr_os_prop_test( data, variable = NULL, prob = 0.5, phat = 0.5, alternative = c("both", "less", "greater", "all") ) # S3 method for default ifr_os_prop_test( data, variable = NULL, prob = 0.5, phat = 0.5, alternative = c("both", "less", "greater", "all") )
data | numeric vector of length 1 or a |
---|---|
variable | factor; column in |
prob | hypothesised proportion |
phat | observed proportion |
alternative | a character string specifying the alternative hypothesis, must be one of "both" (default), "greater", "less" or "all". You can specify just the initial letter. |
ifr_os_prop_test
returns an object of class "ifr_os_prop_test"
.
An object of class "ifr_os_prop_test"
is a list containing the
following components:
number of observations
proportion of 1's
assumed probability of success
z statistic
p-value for z statistic
alternative hypothesis
observed number of 0's and 1's
expected number of 0's and 1's
deviation of observed from expected
standardized resiudals
prop_test()
has been deprecated. Instead use ifr_os_prop_test()
.
Sheskin, D. J. 2007. Handbook of Parametric and Nonparametric Statistical Procedures, 4th edition. : Chapman & Hall/CRC.
# use as a calculator ifr_os_prop_test(200, prob = 0.5, phat = 0.3) #> Test Statistics #> -------------------------- #> Sample Size 200 #> Exp Prop 0.5 #> Obs Prop 0.3 #> z -5.6569 #> Pr(|Z| > |z|) 0 #> #> ----------------------------------------------------------------- #> Category Observed Expected % Deviation Std. Residuals #> ----------------------------------------------------------------- #> 0 140 100 40.00 4.00 #> 1 60 100 -40.00 -4.00 #> ----------------------------------------------------------------- # using data set ifr_os_prop_test(hsb, female, prob = 0.5) #> Test Statistics #> ------------------------- #> Sample Size 200 #> Exp Prop 0.5 #> Obs Prop 0.545 #> z 1.2728 #> Pr(|Z| > |z|) 0.2031 #> #> ----------------------------------------------------------------- #> Category Observed Expected % Deviation Std. Residuals #> ----------------------------------------------------------------- #> 0 91 100 -9.00 -0.90 #> 1 109 100 9.00 0.90 #> -----------------------------------------------------------------