| Type: | Package |
| Title: | Easy Calculation and Visualisation of Confidence Intervals |
| Version: | 2.3.0 |
| Maintainer: | Conor Neilson <condwanaland@gmail.com> |
| Description: | Functions to speed up the exploratory analysis of simple datasets using 'dplyr'. Functions are provided to do the common tasks of calculating confidence intervals. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| LazyData: | true |
| Imports: | dplyr |
| Suggests: | testthat, covr |
| RoxygenNote: | 7.0.2 |
| URL: | https://github.com/condwanaland/summariser |
| NeedsCompilation: | no |
| Packaged: | 2020-03-30 00:36:29 UTC; apple |
| Author: | Conor Neilson [aut, cre] |
| Repository: | CRAN |
| Date/Publication: | 2020-03-30 09:00:02 UTC |
Calculate summary statistics on a data frame
Description
Functions from dplyr are used to automate the process of calculating basic summary statistics on a data frame. Returned statistics include mean, standard deviation, standard error, count, and 95 confidence intervals from a normal distribution (summary_stats) and from a t-distribution (summary_stats.t)
Usage
summary_stats(data, measure, type)
Arguments
data |
a data frame |
measure |
a numeric variable. Response variable - summary statistics will be returned for this variable |
type |
a string variable. Controls whether a normal or t distribution is used for CI calculation. Defaults to "norm". |
Examples
library(summariser)
library(dplyr)
iris %>%
summary_stats(Sepal.Length)