In jungd/ImproveISCAM: Investigating Statistical Concepts, Applications, and Methods

library(knitr)
knitr::opts_chunk$set(comment = NA, fig.align = 'center', fig.height = 5, fig.width = 5, prompt = FALSE, 
highlight = TRUE, tidy = FALSE, warning = FALSE, message = FALSE, 
tidy.opts=list(blank = TRUE, width.cutoff = 80))

Introduction.

Our statistic class use Investigating Statistical Concepts, Applications, and Methods (ISCAM) by Beth L.Chance and Allan J.Rossman. The way ISCAM also involve with R code but this is not a easy way to use. Therefore, the goal is how to improve ISCAM. If you have ISCAM book, turn to page number 129. The book suggest use their R command to solve the problems.

Description

These functions are provide a graphical representation for visual people to see which area we are compute. Order to use this package, it require install improved ISCAM.

devtools::install_github("jungd/ImproveISCAM", build_vignette = TRUE)

Binomial Probability

Binomial probability refers to the probability that a binomial experiment results in exactly x successes.
For example :

library(ImproveISCAM)
binomprob(3,20,1/3,lower.tail = FALSE)
binomprob(3,20,1/3,lower.tail = TRUE)

As you see from my example, binomial(k,n,pi,TRUE/FALSE). lower.tail = FALSE indicate right tail probability of binomial random variable. lower.tail= TRUE indicate left tail probability of binomial random variable.

Exact Binomial Test and Confidence Interval.

binomtest(3, 13, 1/2, "greater")

binomtest(k,n,pi,"greeter/less/tow.sided") will help you determined right/left tail probability of binomial random variable. As you see the result, it already show null hypothesis and alternative hypothesis with p-value. So you can conclude with your result either reject null hypothesis or not.

For example :

binomtest(3, 13, conf.level=c(90,95))

binomtest(k, conf.level = c( , )) will calculate confidence interval for you.

Normal Probability

The normal distribution is a probability distribution that associates the normal random variable X with a cumulative probability.

For example :

normprob(2, direction="above")

normporb(x, mu, sigma, "above/below/outside/between") will help calculate right.left/two-tailed probability and probability between tow values in normal distribution.

Inverse Normal Probability

InNorm(0.88, direction="above")
InNorm(0.88, direction="between")

InNorm(probability, direction="above/below/outside/between") will calculate your z-score value with right/left/two-tail probability and probability between tow values.

Normal(z-test) Approimation for One Propotion and Confidence Interval(CI)

propztest(2.67, 18, 1/3, "greater")

propztest(k,n,pi, "greater/below/less/two.sided/") will find right/left/two-tailed probabilty of proportion using Normal z-test.

propztest(3, 13, conf.level=c(90,95))

propztest(k,n,conf.level=c( ,)) will hlep you find normal confidce interval.

jungd/ImproveISCAM documentation built on May 20, 2019, 4:24 a.m.