TEST.mean: Test on the mean

Description

TEST.mean() tests hypotheses on the mean of a population.

Usage

TEST.mean(
  x,
  sigma = NULL,
  mu0 = 0,
  alternative = "two.sided",
  digits = 2,
  force.digits = FALSE,
  use.scientific = FALSE,
  data,
  ...
)

Value

A table reporting the results of the test on the population mean. If the variance is unknown, the test is run using percentiles from both the normal and the Student's t distribution.

Arguments

x: An unquoted string identifying the numeric variable whose mean is of interest. x can be the name of a vector in the workspace or the name of one of the columns in the data frame specified in the data argument.
sigma: An optional numeric value specifying the population standard deviation. If NULL (default) the population standard deviation is estimated using the data.
mu0: Numeric value that specifies the null hypothesis to test for (default is 0).
alternative: A length-one character vector specifying the direction of the alternative hypothesis. Allowed values are "two.sided" (population mean differs from mu0; default), or "less" (population mean is lower than mu0), or "greater" (population mean is higher than mu0).
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. If not found in data, x is taken from the environment from which TEST.mean() is called.
...: Additional arguments to be passed to low level functions.

Author

Raffaella Piccarreta raffaella.piccarreta@unibocconi.it

Examples

Run this code

data(MktDATA, package = "UBStats")

# Test on the mean; KNOWN variance
# - Bilateral test
TEST.mean(NStore_Purch, sigma = 9, mu0 = 5, 
          alternative = "two.sided", data = MktDATA)
# - Unilateral test
TEST.mean(NStore_Purch, sigma = 9,mu0 = 5,
          alternative = "greater", data = MktDATA)

# Test on the mean; UNKNOWN variance;
# - Unilateral test
TEST.mean(TotVal, mu0 = 600, alternative = "less",
          data = MktDATA)

# Arguments force.digits and use.scientific
# An input variable taking very low values
SmallX<-MktDATA$AOV/500
# Default output
TEST.mean(SmallX, mu0 = 0.1)
# Request to use the exact number of digits (default, 2)
TEST.mean(SmallX, mu0 = 0.1,force.digits=TRUE)
# Request to allow scientific notation
TEST.mean(SmallX, mu0 = 0.1,use.scientific=TRUE)

# Output results
out.test_mean<-TEST.mean(TotVal, mu0 = 600, alternative = "less",
                         data = MktDATA)