Exact Binomial Test

binomtest calculates performas an exact binomial test and graphs the binomial distribution and/or binomial confidence interval.

Usage

iscambinomtest(
  observed,
  n,
  hypothesized = NULL,
  alternative,
  conf.level = NULL
)

Arguments

observed

The observed number of successes or sample proportion (assumed to be proportion if value less than one.)

n

number of trials.

hypothesized

hypothesized probability of success.

alternative

"less", "greater", or "two.sided"

conf.level

Confidence level for a two-sided confidence interval.

Value

a list of the p-value along with lower and upper bound for the calculated confidence interval.

Examples

iscambinomtest(
  observed = 17,
  n = 25,
  hypothesized = 0.5,
  alternative = "greater"
)

#> 
#> Exact Binomial Test
#> 
#> Data: observed successes = 17, sample size = 25, sample proportion = 0.68
#> 
#> Null hypothesis       : pi = 0.5 
#> Alternative hypothesis: pi > 0.5 
#> p-value: 0.053876 

iscambinomtest(
  observed = 12,
  n = 80,
  hypothesized = 0.10,
  alternative = "two.sided",
  conf.level = 0.95
)

#> 
#> Exact Binomial Test
#> 
#> Data: observed successes = 12, sample size = 80, sample proportion = 0.15
#> 
#> Null hypothesis       : pi = 0.1 
#> Alternative hypothesis: pi <> 0.1 
#> p-value: 0.13575 
#> 95 % Confidence interval for pi: ( 0.079982 , 0.24736 ) 

iscambinomtest(
  observed = 0.14,
  n = 100,
  hypothesized = 0.20,
  alternative = "less"
)

#> 
#> Exact Binomial Test
#> 
#> Data: observed successes = 14, sample size = 100, sample proportion = 0.14
#> 
#> Null hypothesis       : pi = 0.2 
#> Alternative hypothesis: pi < 0.2 
#> p-value: 0.080444 

iscambinomtest(observed = 17, n = 25, conf.level = 0.95)
#> 
#> Exact Binomial Test
#> 
#> Data: observed successes = 17, sample size = 25, sample proportion = 0.68
#> 
#> 95 % Confidence interval for pi: ( 0.465 , 0.8505 ) 


iscambinomtest(observed = 12, n = 80, conf.level = c(0.90, 0.95, 0.99))
#> 
#> Exact Binomial Test
#> 
#> Data: observed successes = 12, sample size = 80, sample proportion = 0.15
#> 
#> 90 % Confidence interval for pi: ( 0.088894 , 0.23168 ) 
#> 95 % Confidence interval for pi: ( 0.079982 , 0.24736 ) 
#> 99 % Confidence interval for pi: ( 0.06429 , 0.27922 )