n_t1samp_interval: Sample Size for One Sample T Confidence Intervals
In nutterb/junkyard: Package development playground

Description Usage Arguments Details Value Author(s)

The $t$-based confidence interval is commonly used in estimating population mean using sample data. It is based on Student's $t$ distribution, an adaptation of the standard normal distribution. n_t1samp_interval provides tools for calculating and illustrating the sample size requirement and other design factors associated with these intervals.

1 2	n_t1samp_interval(E = NULL, n = NULL, s = NULL, alpha = 0.05, optim.max = 1e+09)

`E`	Margin of error
`n`	Sample size
`s`	Sample standard deviation
`alpha`	Significance level (or 1-confidence)
`optim.max`	Maximum value for `optimze` when solving for `n`. The default setting is 1,000,000,000, which is probably higher than anyone will ever need. I may change this in the future for the sake of improving speed.

Exactly one of the parameters n, E, s and alpha must be passed as NULL, and that parameter will be calculated from the others. Notice that alpha has a non-NULL default, so NULL must be explicitly passed if you want it computed.

Returns an object of class HazPwr with subclasses t1samp and est (actual appearance: t1samp_est_HazPwr. The object contains a data frame of the parameters passed to the function (expanded using expand.grid) and the corresponding sample size estimates.

n_est: Exact sample size. When n is not NULL, this will be identical to n.
n: Estimated sample size; the next largest integer after n_est.
E: Margin of error
s: Sample Standard Deviation
alpha: Desired significance level.