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:

categories

levels of x

chisquare

chi square statistic

deviation

deviation of observed from frequency

degrees_of_freedom

chi square degrees of freedom

expected_frequency

expected frequency/proportion

n_levels

number of levels of x

observed_frequency

observed frequency/proportion

pvalue

p-value

sample_size

number of observations

std_residuals

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      
#> -----------------------------------------------------------------