R/prop_test_OLD.R
In jrpriceUPS/Math160UPS: Suite of Functions for Math 160 Classes at the University of Puget Sound
Defines functions
prop_test_OLD
Documented in
prop_test_OLD
#' Proportion Test
#'
#' In this old version, one-sided tests are permitted.
#'
#' This function asks you a sequence of questions in order to execute a proportion test. It finds a confidence interval and a p-value, produces a plot, and indicates how this could be queried directly from R.
#' @export
#' @examples
#' > prop_test()
#' Do you have a single population or are you comparing populations?
#' Possible answers are 'single' and 'comparing'.
#' single
#' How many trials were there in your experiment?
#' 10
#' How many successes were there?
#' 5
#' The statistics for your dataset are:
#' phat = 0.5
#' s = sqrt(0.5*(1-0.5)/10) = 0.1581139
#'
#' What is the theoretical proportion you are testing against (called p_0)?
#' (If you only want a confidence interval, type 'NA')
#' .2
#' What is your desired confidence level?
#' .9
#' Are you doing a one-sided or two-sided test? Possible answers are 'less', 'greater', and 'two-sided'.
#' two-sided
#' The probability of getting this result or more extreme for phat
#' if the proportion really is 0.2 is
#' p = 0.0327935
#'
#' The 90% confidence interval for the population proportion is
#' 0.2224411 < p < 0.7775589
#'
#'
#' You can get this result by typing:
#' binom.test(x = 5, n = 10, p = 0.2, alternative = 'two.sided', conf.level = 0.9)
#'
#'
#'
#'
#'
#'
#' > prop_test()
#' Do you have a single population or are you comparing populations? Possible answers are 'single' and 'comparing'. comparing
#' How many trials were there in your first sample? 15
#' How many successes were there in your first sample? 10
#' How many trials were there in your second sample? 20
#' How many successes were there in your second sample? 10
#' The statistics for your dataset are:
#' phat1 = 0.6666667
#' phat2 = 0.5
#' s = sqrt(0.6666667*(1-0.6666667)/15+0.5*(1-0.5)/20) = 0.1652719
#' What is your desired confidence level? .95
#' Are you checking whether the proportion of the second population is less, greater, or different than the proportion of the first population? Possible answers are 'less', 'greater', and 'different'. greater
#' The probability of getting this result or more extreme for phat2 - phat1 if phat1 really is bigger than phat2 is
#' p = 0.739209
#'
#' The 95% confidence interval for the difference in proportions is
#' -0.5489271 < p2 - p1 < 0.2155937
#'
#'
#' You can get this result by typing:
#' prop.test(c(10,10), c(20,15), alternative = 'greater', conf.level = 0.95)
#'
#' For the confidence interval, you would type:
#' prop.test(c(10,10), c(20,15), alternative = 'two.sided',conf.level = 0.95)
prop_test_OLD <- function(){
cat("Do you have a single population or are you comparing populations?\nPossible answers are 'single' and 'comparing'. \n")
compare = readline()
if(compare=="comparing"){
cat("How many trials were there in your first sample? \n")
n1 = as.numeric(readline())
while(n1!=round(n1) | n1<1){cat('Please choose a whole number greater than zero\n')
cat("How many trials were there in your first sample? \n")
n1 = as.numeric(readline())
}
cat("How many successes were there in your first sample? \n")
X1 = as.numeric(readline())
while(X1!=round(X1) | X1<0 | X1>n1){cat(paste('Please choose a whole number greater than zero but less than ',toString(n1),".",sep=""))
cat("How many successes were there in your first sample? \n")
X1 = as.numeric(readline())
}
phat1 = X1/n1
cat("How many trials were there in your second sample? \n")
n2 = as.numeric(readline())
while(n2!=round(n2) | n2<1){cat('Please choose a whole number greater than zero\n')
cat("How many trials were there in your second sample? \n")
n2 = as.numeric(readline())
}
cat("How many successes were there in your second sample? \n")
X2 = as.numeric(readline())
while(X2!=round(X2) | X2<0 | X2>n2){cat(paste('Please choose a whole number greater than zero but less than ',toString(n2),".\n",sep=""))
cat("How many successes were there in your second sample? \n")
X2 = as.numeric(readline())
}
phat2 = X2/n2
p = (X1 + X2)/(n1 + n2)
s = sqrt(phat1*(1-phat1)/n1 + phat2*(1-phat2)/n2)
cat("The statistics for your dataset are: ")
cat("\n")
cat(paste("phat1 =",format(phat1,scientific=FALSE)))
cat("\n")
cat(paste("phat2 =",format(phat2,scientific=FALSE)))
cat("\n")
cat(paste("s = sqrt(",format(phat1,scientific=FALSE),"*(1-",format(phat1,scientific=FALSE),")/",format(n1,scientific=FALSE),"+",format(phat2,scientific=FALSE),"*(1-",format(phat2,scientific=FALSE),")/",format(n2,scientific=FALSE),") = ",format(s,scientific=FALSE),sep=""))
cat("\n")
cat("What is your desired confidence level? \n")
conf_level = as.numeric(readline())
while(conf_level<0 | conf_level>1){cat('Please choose a confidence level between 0 and 1\n')
cat("What is your desired confidence level? \n")
conf_level = as.numeric(readline())
}
cat("Are you checking whether the proportion of the second population is less, greater,\n")
cat("or different than the proportion of the first population?\n")
cat("(If you only want a confidence interval, type 'NA')\n")
cat("Possible answers are 'less', 'greater', 'different', and 'NA'. \n")
sidedness = readline()
sidedness2=sidedness
if(sidedness=="different"){
sidedness = "two.sided"
sidedness2 = "both"
}
if(sidedness!="NA"){
out = prop.test(c(X2,X1),c(n2,n1),alternative=sidedness,conf.level=conf_level)
normal_p(X2/n2-X1/n1, 0, sqrt(p*(1-p)*(1/n1+1/n2)), sidedness2, print = FALSE)}
out_conf = binom.test(c(X2,X1),c(n2,n1),alternative="two.sided",conf.level=conf_level)
if(sidedness=="two.sided"){
first_statement = paste("The probability of getting this result or more extreme for phat2 - phat1 if there really is no difference is")
}
if(sidedness=="less"){
first_statement = paste("The probability of getting this result or more extreme for phat2 - phat1 if phat1 really is bigger than phat2 is")
}
if(sidedness=="greater"){
first_statement = paste("The probability of getting this result or more extreme for phat2 - phat1 if phat1 really is bigger than phat2 is")
}
if(sidedness!="NA"){
cat(first_statement)
cat("\n")
cat(paste("p = ",format(out$p.value,scientific=FALSE)))
cat("\n")
cat("\n")}
cat(paste("The ",toString(conf_level*100),"% confidence interval for the difference in proportions is",sep=""))
cat("\n")
cat(paste(format(out_conf$conf.int[1],scientific=FALSE)," < p2 - p1 < ",format(out_conf$conf.int[2],scientific=FALSE)))
if(sidedness!="NA"){cat("\n")
cat("\n")
cat("\n")
cat("You can get this result by typing:")
cat("\n")
cat(paste("prop.test(c(",format(X2,scientific=FALSE),",",format(X1,scientific=FALSE),"), c(",format(n2,scientific=FALSE),",",format(n1,scientific=FALSE),"), alternative = '",sidedness,"', conf.level = ",format(conf_level,scientific=FALSE), ")",sep=""))
}
if(sidedness!="two.sided"){
cat("\n")
cat("\n")
cat("For the confidence interval, you would type:")
cat("\n")
cat(paste("prop.test(c(",format(X2,scientific=FALSE),",",format(X1,scientific=FALSE),"), c(",format(n2,scientific=FALSE),",",format(n1,scientific=FALSE),"), alternative = 'two.sided',", "conf.level = ",format(conf_level,scientific=FALSE), ")",sep=""))
}
}
if(compare=="single"){
cat("How many trials were there in your experiment? \n")
n = as.numeric(readline())
while(n!=round(n) | n<1){cat('Please choose a whole number greater than zero')
cat("How many trials were there in your experiment? \n")
n = as.numeric(readline())
}
cat("How many successes were there? \n")
X = as.numeric(readline())
while(X!=round(X) | X<0 | X>n){cat(paste('Please choose a whole number greater than zero but less than ',toString(n),".\n",sep=""))
cat("How many successes were there? \n")
X = as.numeric(readline())}
phat = X/n
s = sqrt(phat*(1-phat)/n)
cat("The statistics for your dataset are: ")
cat("\n")
cat(paste("phat =",format(phat,scientific=FALSE)))
cat("\n")
cat(paste("s = sqrt(",format(phat,scientific=FALSE),"*(1-",format(phat,scientific=FALSE),")/",format(n,scientific=FALSE),") = ",format(s,scientific=FALSE),sep=""))
cat("\n\nWhat is the theoretical proportion you are testing against (called p_0)? \n")
cat("(If you only want a confidence interval, type 'NA')\n")
p_0 = readline()
if(p_0!="NA"){p_0=as.numeric(p_0)}
cat("What is your desired confidence level? \n")
conf_level = as.numeric(readline())
while(conf_level<0 | conf_level>1){cat('Please choose a confidence level between 0 and 1\n')
cat("What is your desired confidence level? \n")
conf_level = as.numeric(readline())
}
if(p_0!="NA"){
cat("Are you doing a one-sided or two-sided test? Possible answers are 'less', 'greater', and 'two-sided'. \n")
sidedness = readline()
if(sidedness == "t"){sidedness = "two-sided"}
if(sidedness == "g"){sidedness = "greater"}
if(sidedness == "l"){sidedness = "less"}
while(sidedness != "two-sided" & sidedness != "greater" & sidedness != "less"){cat("Please choose one of 'less', 'greater', and 'two-sided'.\n")
cat("Are you doing a one-sided or two-sided test? Possible answers are 'less', 'greater', and 'two-sided'. \n")
sidedness = readline()
}
sidedness2=sidedness
if(sidedness=="two-sided"){
sidedness = "two.sided"
sidedness2 = "both"
}
out = binom.test(X,n,p=p_0,alternative=sidedness)}
if(p_0!="NA"){
out_conf = binom.test(X,n,p=p_0,alternative="two.sided", conf.level = conf_level)}
if(p_0=="NA"){out_conf = binom.test(X,n,p=0.5,alternative="two.sided",conf.level = conf_level)}
if(p_0!="NA"){
if(n>=100){
normal_p(X/n, p_0, s, sidedness2, print = FALSE)
}
if(n<100){
cols = rep("gray",n+1)
if(sidedness == "less"){
cols[1:(X+1)] = rep("skyblue",X+1)
word = "less"
}
if(sidedness == "greater"){
cols[(X+1):(n+1)] = rep("skyblue",n-X+1)
word = "greater"
}
if(sidedness == "two.sided"){
if(X<=p_0*n){
Y = min(c(p_0*n+(p_0*n-X),n))
newX = X
}
if(X>=p_0*n){
Y = X
newX = max(c(p_0*n-(Y - p_0*n),0))
}
cols = rep("gray",n+1)
cols[1:(newX+1)] = rep("skyblue",newX+1)
cols[(Y+1):(n+1)] = rep("skyblue",n-Y+1)
word = "more extreme"
}
barplot(dbinom(0:n,n,p_0),names = c(0:n),col=cols)
}
}
if(p_0!="NA"){
cat(paste("The probability of getting this result or ",word," for phat\nif the proportion really is ",format(p_0,scientific=FALSE)," is ",sep=""))
cat("\n")
cat(paste("p = ",format(out$p.value,scientific=FALSE)))
cat("\n")
cat("\n")}
cat(paste("The ",toString(conf_level*100),"% confidence interval for the population proportion is",sep=""))
cat("\n")
cat(paste(format(out_conf$conf.int[1],scientific=FALSE)," < p < ",format(out_conf$conf.int[2],scientific=FALSE)))
cat("\n")
cat("\n")
cat("\n")
cat("You can get this result by typing:")
cat("\n")
if(p_0!="NA"){
cat(paste("binom.test(x = ",format(X,scientific=FALSE),", n = ",format(n,scientific=FALSE),", p = ",format(p_0,scientific=FALSE),", alternative = '",sidedness,"', conf.level = ", format(conf_level,scientific=FALSE),")",sep=""))
}
if(p_0 == "NA"){
cat(paste("binom.test(x = ",format(X,scientific=FALSE),", n = ",format(n,scientific=FALSE),", conf.level = ", format(conf_level,scientific=FALSE),")",sep=""))
}
if(p_0!="NA"){
if(sidedness!="two.sided"){
cat("\n")
cat("\n")
cat("For the confidence interval, you would type:")
cat("\n")
cat(paste("binom.test(x = ",format(X,scientific=FALSE),", n = ",format(n,scientific=FALSE),", p = ",format(p_0,scientific=FALSE),", alternative = 'two.sided', conf.level = ", format(conf_level,scientific=FALSE),")",sep=""))
}}
}
}
jrpriceUPS/Math160UPS documentation built on April 28, 2024, 12:41 p.m.
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Defines functions prop_test_OLD
Documented in prop_test_OLD
#' Proportion Test
#'
#' In this old version, one-sided tests are permitted.
#'
#' This function asks you a sequence of questions in order to execute a proportion test. It finds a confidence interval and a p-value, produces a plot, and indicates how this could be queried directly from R.
#' @export
#' @examples
#' > prop_test()
#' Do you have a single population or are you comparing populations?
#' Possible answers are 'single' and 'comparing'.
#' single
#' How many trials were there in your experiment?
#' 10
#' How many successes were there?
#' 5
#' The statistics for your dataset are:
#' phat = 0.5
#' s = sqrt(0.5*(1-0.5)/10) = 0.1581139
#'
#' What is the theoretical proportion you are testing against (called p_0)?
#' (If you only want a confidence interval, type 'NA')
#' .2
#' What is your desired confidence level?
#' .9
#' Are you doing a one-sided or two-sided test? Possible answers are 'less', 'greater', and 'two-sided'.
#' two-sided
#' The probability of getting this result or more extreme for phat
#' if the proportion really is 0.2 is
#' p = 0.0327935
#'
#' The 90% confidence interval for the population proportion is
#' 0.2224411 < p < 0.7775589
#'
#'
#' You can get this result by typing:
#' binom.test(x = 5, n = 10, p = 0.2, alternative = 'two.sided', conf.level = 0.9)
#'
#'
#'
#'
#'
#'
#' > prop_test()
#' Do you have a single population or are you comparing populations? Possible answers are 'single' and 'comparing'. comparing
#' How many trials were there in your first sample? 15
#' How many successes were there in your first sample? 10
#' How many trials were there in your second sample? 20
#' How many successes were there in your second sample? 10
#' The statistics for your dataset are:
#' phat1 = 0.6666667
#' phat2 = 0.5
#' s = sqrt(0.6666667*(1-0.6666667)/15+0.5*(1-0.5)/20) = 0.1652719
#' What is your desired confidence level? .95
#' Are you checking whether the proportion of the second population is less, greater, or different than the proportion of the first population? Possible answers are 'less', 'greater', and 'different'. greater
#' The probability of getting this result or more extreme for phat2 - phat1 if phat1 really is bigger than phat2 is
#' p = 0.739209
#'
#' The 95% confidence interval for the difference in proportions is
#' -0.5489271 < p2 - p1 < 0.2155937
#'
#'
#' You can get this result by typing:
#' prop.test(c(10,10), c(20,15), alternative = 'greater', conf.level = 0.95)
#'
#' For the confidence interval, you would type:
#' prop.test(c(10,10), c(20,15), alternative = 'two.sided',conf.level = 0.95)
prop_test_OLD <- function(){
cat("Do you have a single population or are you comparing populations?\nPossible answers are 'single' and 'comparing'. \n")
compare = readline()
if(compare=="comparing"){
cat("How many trials were there in your first sample? \n")
n1 = as.numeric(readline())
while(n1!=round(n1) | n1<1){cat('Please choose a whole number greater than zero\n')
cat("How many trials were there in your first sample? \n")
n1 = as.numeric(readline())
}
cat("How many successes were there in your first sample? \n")
X1 = as.numeric(readline())
while(X1!=round(X1) | X1<0 | X1>n1){cat(paste('Please choose a whole number greater than zero but less than ',toString(n1),".",sep=""))
cat("How many successes were there in your first sample? \n")
X1 = as.numeric(readline())
}
phat1 = X1/n1
cat("How many trials were there in your second sample? \n")
n2 = as.numeric(readline())
while(n2!=round(n2) | n2<1){cat('Please choose a whole number greater than zero\n')
cat("How many trials were there in your second sample? \n")
n2 = as.numeric(readline())
}
cat("How many successes were there in your second sample? \n")
X2 = as.numeric(readline())
while(X2!=round(X2) | X2<0 | X2>n2){cat(paste('Please choose a whole number greater than zero but less than ',toString(n2),".\n",sep=""))
cat("How many successes were there in your second sample? \n")
X2 = as.numeric(readline())
}
phat2 = X2/n2
p = (X1 + X2)/(n1 + n2)
s = sqrt(phat1*(1-phat1)/n1 + phat2*(1-phat2)/n2)
cat("The statistics for your dataset are: ")
cat("\n")
cat(paste("phat1 =",format(phat1,scientific=FALSE)))
cat("\n")
cat(paste("phat2 =",format(phat2,scientific=FALSE)))
cat("\n")
cat(paste("s = sqrt(",format(phat1,scientific=FALSE),"*(1-",format(phat1,scientific=FALSE),")/",format(n1,scientific=FALSE),"+",format(phat2,scientific=FALSE),"*(1-",format(phat2,scientific=FALSE),")/",format(n2,scientific=FALSE),") = ",format(s,scientific=FALSE),sep=""))
cat("\n")
cat("What is your desired confidence level? \n")
conf_level = as.numeric(readline())
while(conf_level<0 | conf_level>1){cat('Please choose a confidence level between 0 and 1\n')
cat("What is your desired confidence level? \n")
conf_level = as.numeric(readline())
}
cat("Are you checking whether the proportion of the second population is less, greater,\n")
cat("or different than the proportion of the first population?\n")
cat("(If you only want a confidence interval, type 'NA')\n")
cat("Possible answers are 'less', 'greater', 'different', and 'NA'. \n")
sidedness = readline()
sidedness2=sidedness
if(sidedness=="different"){
sidedness = "two.sided"
sidedness2 = "both"
}
if(sidedness!="NA"){
out = prop.test(c(X2,X1),c(n2,n1),alternative=sidedness,conf.level=conf_level)
normal_p(X2/n2-X1/n1, 0, sqrt(p*(1-p)*(1/n1+1/n2)), sidedness2, print = FALSE)}
out_conf = binom.test(c(X2,X1),c(n2,n1),alternative="two.sided",conf.level=conf_level)
if(sidedness=="two.sided"){
first_statement = paste("The probability of getting this result or more extreme for phat2 - phat1 if there really is no difference is")
}
if(sidedness=="less"){
first_statement = paste("The probability of getting this result or more extreme for phat2 - phat1 if phat1 really is bigger than phat2 is")
}
if(sidedness=="greater"){
first_statement = paste("The probability of getting this result or more extreme for phat2 - phat1 if phat1 really is bigger than phat2 is")
}
if(sidedness!="NA"){
cat(first_statement)
cat("\n")
cat(paste("p = ",format(out$p.value,scientific=FALSE)))
cat("\n")
cat("\n")}
cat(paste("The ",toString(conf_level*100),"% confidence interval for the difference in proportions is",sep=""))
cat("\n")
cat(paste(format(out_conf$conf.int[1],scientific=FALSE)," < p2 - p1 < ",format(out_conf$conf.int[2],scientific=FALSE)))
if(sidedness!="NA"){cat("\n")
cat("\n")
cat("\n")
cat("You can get this result by typing:")
cat("\n")
cat(paste("prop.test(c(",format(X2,scientific=FALSE),",",format(X1,scientific=FALSE),"), c(",format(n2,scientific=FALSE),",",format(n1,scientific=FALSE),"), alternative = '",sidedness,"', conf.level = ",format(conf_level,scientific=FALSE), ")",sep=""))
}
if(sidedness!="two.sided"){
cat("\n")
cat("\n")
cat("For the confidence interval, you would type:")
cat("\n")
cat(paste("prop.test(c(",format(X2,scientific=FALSE),",",format(X1,scientific=FALSE),"), c(",format(n2,scientific=FALSE),",",format(n1,scientific=FALSE),"), alternative = 'two.sided',", "conf.level = ",format(conf_level,scientific=FALSE), ")",sep=""))
}
}
if(compare=="single"){
cat("How many trials were there in your experiment? \n")
n = as.numeric(readline())
while(n!=round(n) | n<1){cat('Please choose a whole number greater than zero')
cat("How many trials were there in your experiment? \n")
n = as.numeric(readline())
}
cat("How many successes were there? \n")
X = as.numeric(readline())
while(X!=round(X) | X<0 | X>n){cat(paste('Please choose a whole number greater than zero but less than ',toString(n),".\n",sep=""))
cat("How many successes were there? \n")
X = as.numeric(readline())}
phat = X/n
s = sqrt(phat*(1-phat)/n)
cat("The statistics for your dataset are: ")
cat("\n")
cat(paste("phat =",format(phat,scientific=FALSE)))
cat("\n")
cat(paste("s = sqrt(",format(phat,scientific=FALSE),"*(1-",format(phat,scientific=FALSE),")/",format(n,scientific=FALSE),") = ",format(s,scientific=FALSE),sep=""))
cat("\n\nWhat is the theoretical proportion you are testing against (called p_0)? \n")
cat("(If you only want a confidence interval, type 'NA')\n")
p_0 = readline()
if(p_0!="NA"){p_0=as.numeric(p_0)}
cat("What is your desired confidence level? \n")
conf_level = as.numeric(readline())
while(conf_level<0 | conf_level>1){cat('Please choose a confidence level between 0 and 1\n')
cat("What is your desired confidence level? \n")
conf_level = as.numeric(readline())
}
if(p_0!="NA"){
cat("Are you doing a one-sided or two-sided test? Possible answers are 'less', 'greater', and 'two-sided'. \n")
sidedness = readline()
if(sidedness == "t"){sidedness = "two-sided"}
if(sidedness == "g"){sidedness = "greater"}
if(sidedness == "l"){sidedness = "less"}
while(sidedness != "two-sided" & sidedness != "greater" & sidedness != "less"){cat("Please choose one of 'less', 'greater', and 'two-sided'.\n")
cat("Are you doing a one-sided or two-sided test? Possible answers are 'less', 'greater', and 'two-sided'. \n")
sidedness = readline()
}
sidedness2=sidedness
if(sidedness=="two-sided"){
sidedness = "two.sided"
sidedness2 = "both"
}
out = binom.test(X,n,p=p_0,alternative=sidedness)}
if(p_0!="NA"){
out_conf = binom.test(X,n,p=p_0,alternative="two.sided", conf.level = conf_level)}
if(p_0=="NA"){out_conf = binom.test(X,n,p=0.5,alternative="two.sided",conf.level = conf_level)}
if(p_0!="NA"){
if(n>=100){
normal_p(X/n, p_0, s, sidedness2, print = FALSE)
}
if(n<100){
cols = rep("gray",n+1)
if(sidedness == "less"){
cols[1:(X+1)] = rep("skyblue",X+1)
word = "less"
}
if(sidedness == "greater"){
cols[(X+1):(n+1)] = rep("skyblue",n-X+1)
word = "greater"
}
if(sidedness == "two.sided"){
if(X<=p_0*n){
Y = min(c(p_0*n+(p_0*n-X),n))
newX = X
}
if(X>=p_0*n){
Y = X
newX = max(c(p_0*n-(Y - p_0*n),0))
}
cols = rep("gray",n+1)
cols[1:(newX+1)] = rep("skyblue",newX+1)
cols[(Y+1):(n+1)] = rep("skyblue",n-Y+1)
word = "more extreme"
}
barplot(dbinom(0:n,n,p_0),names = c(0:n),col=cols)
}
}
if(p_0!="NA"){
cat(paste("The probability of getting this result or ",word," for phat\nif the proportion really is ",format(p_0,scientific=FALSE)," is ",sep=""))
cat("\n")
cat(paste("p = ",format(out$p.value,scientific=FALSE)))
cat("\n")
cat("\n")}
cat(paste("The ",toString(conf_level*100),"% confidence interval for the population proportion is",sep=""))
cat("\n")
cat(paste(format(out_conf$conf.int[1],scientific=FALSE)," < p < ",format(out_conf$conf.int[2],scientific=FALSE)))
cat("\n")
cat("\n")
cat("\n")
cat("You can get this result by typing:")
cat("\n")
if(p_0!="NA"){
cat(paste("binom.test(x = ",format(X,scientific=FALSE),", n = ",format(n,scientific=FALSE),", p = ",format(p_0,scientific=FALSE),", alternative = '",sidedness,"', conf.level = ", format(conf_level,scientific=FALSE),")",sep=""))
}
if(p_0 == "NA"){
cat(paste("binom.test(x = ",format(X,scientific=FALSE),", n = ",format(n,scientific=FALSE),", conf.level = ", format(conf_level,scientific=FALSE),")",sep=""))
}
if(p_0!="NA"){
if(sidedness!="two.sided"){
cat("\n")
cat("\n")
cat("For the confidence interval, you would type:")
cat("\n")
cat(paste("binom.test(x = ",format(X,scientific=FALSE),", n = ",format(n,scientific=FALSE),", p = ",format(p_0,scientific=FALSE),", alternative = 'two.sided', conf.level = ", format(conf_level,scientific=FALSE),")",sep=""))
}}
}
}
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