README.md

In azc242/collegestats: Common functions used in college statistics classes

collegestats

A package originally designed for ECON-18 statistics course at NYU, but contains useful R functions for most university statistics classes.

Installation

If you don't have devtools installed, you can do so by running the following code in your terminal or RStudio. If you have devtools installed, just run the second line to install collegestats.

install.packages("devtools")
devtools::install_github("azc242/collegestats")

Troubleshooting

Trouble installing: Refresh RStudio (ctrl/cmd + shift + F10), close RStudio, and retry.

Show usage/docs: help(package = collegestats). This will only work if you have the package installed aready.

Functions

z_test_neq(H0, sigma = FALSE, alpha, samp_size, x_bar)

Description: Conducts double sided z-test, equivalent of Ha != H0.

Arguments - H0: Null hyothesis - sigma = (Optional) population standard deviation - samp_size: Sample size - x_bar: Sample mean or proportion

Value Data frame containing test result, p-value, critical values

z_test_leq(H0, sigma = FALSE, alpha, samp_size, x_bar)

Description: Conducts lower-tailed z-test, equivalent of Ha < H0.

Arguments - H0: Null hyothesis - sigma = (Optional) population standard deviation - samp_size: Sample size - x_bar: Sample mean or proportion

Value Data frame containing test result, p-value, critical value

z_test_geq(H0, sigma = FALSE, alpha, samp_size, x_bar)

Description: Conducts upper-tailed z-test, equivalent of Ha > H0

Arguments - H0: Null hyothesis - sigma = (Optional) population standard deviation - samp_size: Sample size - x_bar: Sample mean or proportion

Value Data frame containing test result, p-value, critical value

get_p_value(z_score, two_sided = FALSE)

Note: You should use a z_test() function instead to obtain the p-value if you are also looking for the z-test results.

Description: Gets the p-value

Arguments - z_score: z-score - two_sided: Boolean value denoting whether test is double sided or not, defaults to FALSE

Value P-value

get_z(p_hat, p_null, size, sigma = NULL)

Note: You should use a z_test() function instead to obtain the z-score if you are also looking for the z-test results with the p-value.

Description: Gets the z-score

Arguments - p_hat: Sample probability - p_null: Null hypothesis value - size: Sample size - sigma: (Optional) standard deviation, defaults to NULL

Value Z-score

get_z_given_sd(p_hat, p_null, sd, size)

Note: this function should NOT be used, use get_z() instead and pass the standard deviation as sigma.

Description: Gets the z-score given the standard deviation.

Arguments - p_hat: Sample probability - p-null: Null hypothesis value - sd: Standard deviation - size: Sample size

Value Z-score

interval(trials, successes, conf)

Description: Gets the confidence interval.

Arguments - trials: Number of trials - successes: Number of successes of the trials - conf: Confidence level

Value Confidence level formatted as a String

type_2_err(H0, Ha, p, n, alpha, sigma = NULL)

Description: Gets the probability of making a Type II error. Equivalent to the probability of incorrectly failing to reject the null hypothesis.

Arguments - H0: Null hypothesis - Ha: Direction of the test, valid arguments are either "<", ">", or "!=" - mu_alt: True probability/mean value - n: Sample size - alpha: Significance level/Type I error probability/alpha level - sigma (Optional) population standard deviation

Value Type II error, or Beta

type_2_err_min_size(alpha, beta, H0, Ha, two_sided = FALSE, sigma = NULL)

Description: Gets the minimum sample size required to obtain a desired probability of making a Type II error.

Arguments - alpha: Probability of Type I error - beta: Probability of Type II error desired - H0: Null hypothesis - Ha: Actual mean or probability used with beta - two_sided: (Optional) Boolean value denoting whether test is double sided or not, defaults to FALSE - sigma: (Optional) Standard deviation. Defaults to NULL, for when H0 and Ha are probabilities and not mean values

Value NOT rounded minimum sample size needed (generally round upwards for an upper test)

power(H0, Ha, p, n, alpha, sigma = NULL)

Description: Gets the probability of correctly rejecting the null hypothesis. Equivalent to (1 - Beta), or (1 - the probability of making a type II error).

Arguments - H0: Null hypothesis - Ha: Direction of the test, valid arguments are either "<", ">", or "!=" - mu_alt: True probability/mean value - n: Sample size - alpha: Significance level/Type I error probability/alpha level - sigma (Optional) population standard deviation

Value Power, or 1 - Beta

azc242/collegestats documentation built on Dec. 31, 2020, 7:54 p.m.