UBStats (version 0.2.2)

CI.prop: Confidence intervals for the proportion

Description

CI.prop() builds confidence intervals for the proportion of successes in a population.

Usage

CI.prop(
  x,
  success = NULL,
  conf.level = 0.95,
  digits = 2,
  force.digits = FALSE,
  use.scientific = FALSE,
  data,
  ...
)

Value

A table reporting the confidence intervals for the population proportion of successes.

Arguments

x

An unquoted string identifying the variable of interest. x can be the name of a vector or a factor in the workspace or the name of one of the columns in the data frame specified in the data argument.

success

If x is a factor, a character vector, or a numeric non-binary vector, success must be used to indicate the category/value corresponding to success. The argument can be omitted (NULL, default) if x is a binary numeric vector (takes values 0 or 1 only; in this case success is assumed to be 1) or a logical vector (in these cases success is assumed to be TRUE).

conf.level

Numeric value specifying the required confidence level; default to 0.95.

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 CI.prop() is called.

...

Additional arguments to be passed to low level functions.

Author

Raffaella Piccarreta

See Also

TEST.prop() to test hypotheses on the proportion of successes in a population.

Examples

data(MktDATA, package = "UBStats")

# Success = one value of a character vector or factor
CI.prop(WouldSuggest, success = "Yes", data = MktDATA)

# - change confidence level and rounding
CI.prop(Education, success = "Post-Grad", 
        conf.level = 0.9, digits = 4, 
        data = MktDATA)

# Success = numeric value
CI.prop(Children, success = 2, data = MktDATA)

# Binary variable ('success' is 1 by default)
CI.prop(LastCampaign, digits = 3, data = MktDATA)

# Logical variable ('success' is TRUE by default)
CI.prop(RespCampaign, conf.level = 0.9, digits = 3, data = MktDATA)

# Success based on combined conditions
# - Build a (logical) vector indicating whether a condition is satisfied
IsTop <- MktDATA$CustClass == "Gold" | MktDATA$CustClass == "Platinum"
CI.prop(IsTop, conf.level = 0.9)
# - A very rare event
HighAOV <- MktDATA$AOV>150
CI.prop(HighAOV, conf.level = 0.9)

# Arguments force.digits, use.scientific
# - Default: manages possible excess of rounding
CI.prop(HighAOV)
# - Forcing digits to the default values (2)
CI.prop(HighAOV, force.digits = TRUE)
# - Allow scientific notation
CI.prop(HighAOV, use.scientific = TRUE)

# Output results
out_ci_prop<-CI.prop(HighAOV)