UBStats (version 0.2.2)

TEST.diffvar: Tests on variances

Description

TEST.diffvar() tests the hypothesis of equality between the variances of two independent populations.

Usage

TEST.diffvar(
  x,
  y,
  by,
  digits = 2,
  force.digits = FALSE,
  use.scientific = FALSE,
  data,
  ...
)

Value

A table reporting the results of the test on the difference between the variances of two independent populations.

Arguments

x, y

Unquoted strings identifying the numeric variables with the same length whose variances have to be compared. x and y can be the names of vectors in the workspace or the names of columns in the data frame specified in the data argument. It is possible to use a mixed specification (e.g, one vector and one column in data).

by

Optional unquoted string identifying a variable (of any type), defined same way as x, taking only two values used to split x into two independent samples. Since the null hypothesis of equal variances is tested against the bilateral alternative only, the order of the levels of by is irrelevant (differently from what holds for functions building confidence intervals or testing hypotheses on the differences between means or proportions). Note that only one between y and by can be specified.

digits

Integer value specifying the number of decimals used to round statistics; default to 2. If the chosen rounding formats some non-zero values as zero, the number of decimals is increased so that all values have at least one significant digit, unless the argument force.digits is set to TRUE.

force.digits

Logical value indicating whether reported values should be forcedly rounded to the number of decimals specified in digits even if non-zero values are rounded to zero (default to FALSE).

use.scientific

Logical value indicating whether numbers in tables should be displayed using scientific notation (TRUE); default to FALSE.

data

An optional data frame containing x and/or y. If not found in data, the variables are taken from the environment from which TEST.diffvar() is called.

...

Additional arguments to be passed to low level functions.

Author

Raffaella Piccarreta

See Also

CI.diffmean() to build confidence intervals for the difference between two populations' means.

TEST.diffmean() to test hypotheses on the difference between two populations' means.

Examples

data(MktDATA, package = "UBStats")

# Using x,y: build vectors with data on the two groups
AOV_M <- MktDATA$AOV[MktDATA$Gender == "M"]
AOV_F <- MktDATA$AOV[MktDATA$Gender == "F"]
TEST.diffvar(x = AOV_M, y = AOV_F)
TEST.diffvar(x = AOV_F, y = AOV_M) # same

# Using x,by: groups identified by ordered levels of by
TEST.diffvar(x = AOV, by = Gender, data=MktDATA)

# Output results
out_test.diffV<-TEST.diffvar(x = AOV_M, y = AOV_F)

# Arguments force.digits and use.scientific
#  An input variable taking very low values
SmallX<-MktDATA$AOV/50000
SmallX_M <- SmallX[MktDATA$Gender == "M"]
SmallX_F <- SmallX[MktDATA$Gender == "F"]
#  - Default output
TEST.diffvar(x = SmallX_M, y = SmallX_F)
#  - Request to use the exact number of digits (default, 2)
TEST.diffvar(x = SmallX_M, y = SmallX_F,
             force.digits = TRUE)
#  - Request to allow scientific notation
TEST.diffvar(x = SmallX_M, y = SmallX_F, 
             use.scientific = TRUE)