ifr_os_var_test
performs tests on the equality of standard
deviations (variances).It tests that the standard deviation of a sample is
equal to a hypothesized value.
Usage
ifr_os_var_test(
data,
x,
sd,
confint = 0.95,
alternative = c("both", "less", "greater", "all"),
...
)
Arguments
- data
a
data.frame
ortibble
- x
numeric; column in
data
- sd
hypothesised standard deviation
- confint
confidence level
- 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
- ...
additional arguments passed to or from other methods
Value
ifr_os_var_test
returns an object of class "ifr_os_var_test"
.
An object of class "ifr_os_var_test"
is a list containing the
following components:
- n
number of observations
- sd
hypothesised standard deviation of
x
- sigma
observed standard deviation
- se
estimated standard error
- chi
chi-square statistic
- df
degrees of freedom
- p_lower
lower one-sided p-value
- p_upper
upper one-sided p-value
- p_two
two-sided p-value
- xbar
mean of
x
- c_lwr
lower confidence limit of standard deviation
- c_upr
upper confidence limit of standard deviation
- var_name
name of
x
- conf
confidence level
- type
alternative hypothesis
References
Sheskin, D. J. 2007. Handbook of Parametric and Nonparametric Statistical Procedures, 4th edition. : Chapman & Hall/CRC.
Examples
# lower tail
ifr_os_var_test(mtcars, mpg, 5, alternative = 'less')
#> One-Sample Statistics
#> -----------------------------------------------------------------------------
#> Variable Obs Mean Std. Err. Std. Dev. [95% Conf. Interval]
#> -----------------------------------------------------------------------------
#> mpg 32 20.0906 1.0654 6.0269 3.8737 10.6527
#> -----------------------------------------------------------------------------
#>
#> Lower Tail Test
#> ---------------
#> Ho: sd(mpg) >= 5
#> Ha: sd(mpg) < 5
#>
#> Chi-Square Test for Variance
#> -------------------------------------
#> Variable c DF Sig
#> -------------------------------------
#> mpg 45.042 31 0.9506
#> -------------------------------------
# upper tail
ifr_os_var_test(mtcars, mpg, 5, alternative = 'greater')
#> One-Sample Statistics
#> -----------------------------------------------------------------------------
#> Variable Obs Mean Std. Err. Std. Dev. [95% Conf. Interval]
#> -----------------------------------------------------------------------------
#> mpg 32 20.0906 1.0654 6.0269 3.8737 10.6527
#> -----------------------------------------------------------------------------
#>
#> Upper Tail Test
#> ---------------
#> Ho: sd(mpg) <= 5
#> Ha: sd(mpg) > 5
#>
#> Chi-Square Test for Variance
#> -------------------------------------
#> Variable c DF Sig
#> -------------------------------------
#> mpg 45.042 31 0.0494
#> -------------------------------------
# both tails
ifr_os_var_test(mtcars, mpg, 5, alternative = 'both')
#> One-Sample Statistics
#> -----------------------------------------------------------------------------
#> Variable Obs Mean Std. Err. Std. Dev. [95% Conf. Interval]
#> -----------------------------------------------------------------------------
#> mpg 32 20.0906 1.0654 6.0269 3.8737 10.6527
#> -----------------------------------------------------------------------------
#>
#> Two Tail Test
#> ---------------
#> Ho: sd(mpg) = 5
#> Ha: sd(mpg) != 5
#>
#> Chi-Square Test for Variance
#> -------------------------------------
#> Variable c DF Sig
#> -------------------------------------
#> mpg 45.042 31 0.0988
#> -------------------------------------
# all tails
ifr_os_var_test(mtcars, mpg, 5, alternative = 'all')
#> One-Sample Statistics
#> -----------------------------------------------------------------------------
#> Variable Obs Mean Std. Err. Std. Dev. [95% Conf. Interval]
#> -----------------------------------------------------------------------------
#> mpg 32 20.0906 1.0654 6.0269 3.8737 10.6527
#> -----------------------------------------------------------------------------
#>
#> Ho: sd(mpg) = 5
#>
#> Ha: sd < 5 Ha: sd != 5 Ha: sd > 5
#> c = 45.0419 c = 45.0419 c = 45.0419
#> Pr(C < c) = 0.9506 2 * Pr(C > c) = 0.0988 Pr(C > c) = 0.0494