Test whether the observed proportions for a categorical variable differ from hypothesized proportions

infer_chisq_gof_test(data, x, y, correct = FALSE)

Arguments

data

a data.frame or tibble

x

factor; column in data

y

expected proportions

correct

logical; if TRUE continuity correction is applied

Value

infer_chisq_gof_test returns an object of class "infer_chisq_gof_test". An object of class "infer_chisq_gof_test" is a list containing the following components:

chisquare

chi square statistic

pvalue

p-value

df

chi square degrees of freedom

ssize

number of observations

names

levels of x

level

number of levels of x

obs

observed frequency/proportion

exp

expected frequency/proportion

deviation

deviation of observed from frequency

std

standardized residuals

varname

name of categorical variable

Deprecated Function

chisq_gof() has been deprecated. Instead use infer_chisq_gof_test()

References

Sheskin, D. J. 2007. Handbook of Parametric and Nonparametric Statistical Procedures, 4th edition. : Chapman & Hall/CRC.

See also

Examples

infer_chisq_gof_test(hsb, race, c(20, 20, 20, 140))
#> Test Statistics #> ----------------------- #> Chi-Square 5.0286 #> DF 3 #> Pr > Chi Sq 0.1697 #> Sample Size 200 #> #> Variable: race #> ----------------------------------------------------------------- #> Category Observed Expected % Deviation Std. Residuals #> ----------------------------------------------------------------- #> 1 24 20 20.00 0.89 #> 2 11 20 -45.00 -2.01 #> 3 20 20 0.00 0.00 #> 4 145 140 3.57 0.42 #> -----------------------------------------------------------------
# apply continuity correction infer_chisq_gof_test(hsb, race, c(20, 20, 20, 140), correct = TRUE)
#> Test Statistics #> ----------------------- #> Chi-Square 4.3821 #> DF 3 #> Pr > Chi Sq 0.2231 #> Sample Size 200 #> #> Variable: race #> ----------------------------------------------------------------- #> Category Observed Expected % Deviation Std. Residuals #> ----------------------------------------------------------------- #> 1 24 20 17.50 0.78 #> 2 11 20 -47.50 -2.12 #> 3 20 20 -2.50 -0.11 #> 4 145 140 3.21 0.38 #> -----------------------------------------------------------------