README.md

In SophieSXR/Workout03: Binomial Distribution

Overview

binomial is a package that provides functions for bino mial distributions.

• bin_choose() calculates the number of combinations in which k successes can occur in n trials.

• bin_probability() calculates the probability in which k successes can occur in n trials with the probability of success.

• bin_distribution() calculates the binomial distribution with an output as a data frame with class "bindis","data.frame".

• plot() method for a binomial distribution creates a barplot.

• bin_cumulative() calculates the cumulative probability of a binomial distribution. The output is a data frame with class "bincum","data.frame".

• plot() function gives you a line plot of the cumulative distribution.

• bin_variable() gives the binomial variable with class "binvar". It prints out the parameters.

• summary() functions gives you a summary of the variable: mean, variable, mode, skewness, kurtosis.

• bin_mean() calculates mean of binomial distributions.

• bin_variance() calculates variance of binomial.

• bin_mode() calculates mode of binomial distributions.

• bin_skewness() calculates skewness of binomial distributions.

• bin_kurtosis() calculates kurtosis of binomial distributions

Motivation

This package has been developed for the model of binomial distribution.

Usage

library(binomial)

bin_choose(n = 5, k = 2)

## [1] 10

# probability of getting 2 successes in 5 trials
# (assuming prob of success = 0.5) 
bin_probability(success = 2, trials = 5, prob = 0.5)

## [1] 0.3125

bin_distribution(trials=5, prob = 0.5)

##   success probability
## 1       0     0.03125
## 2       1     0.15625
## 3       2     0.31250
## 4       3     0.31250
## 5       4     0.15625
## 6       5     0.03125

dis1 <- bin_distribution(trials = 5, prob = 0.5)
plot(dis1)

bin_cumulative(trials=5, prob = 0.5)

##   success probability cumulative
## 1       0     0.03125    0.03125
## 2       1     0.15625    0.18750
## 3       2     0.31250    0.50000
## 4       3     0.31250    0.81250
## 5       4     0.15625    0.96875
## 6       5     0.03125    1.00000

dis2 <- bin_cumulative(trials = 5, prob = 0.5)
plot(dis2)

bin_variable(trials = 10, p = 0.3)

## "Binomial variable"
## 
## Parameters
## - number of trials:  10 
## - prob of success:  0.3

bin1 <- bin_variable(trials = 10, p = 0.3)
binsum1 <- summary(bin1)
binsum1

## "Summary Binomial"
## 
## Parameters
## - number of trials:  10 
## - prob of success:  0.3 
## 
## Measures
## - mean:  3 
## - variance:  2.1 
## - mode:  3 
## - skewness:  0.2760262 
## - kurtosis:  -0.1238095

bin_mean(trials = 10, prob = 0.3)

## [1] 3

bin_variance(trials = 10, prob = 0.3)

## [1] 2.1

bin_mode(trials = 10, prob = 0.3)

## [1] 3

bin_skewness(trials = 10, prob = 0.3)

## [1] 0.2760262

bin_kurtosis(trials = 10, prob = 0.3)

## [1] -0.1238095

SophieSXR/Workout03 documentation built on May 4, 2019, 12:54 a.m.