Packaged: 2022-04-23 19:52:03 UTC; davidgerbing

Description: Each function accomplishes the work of several or more standard R functions. For example, two function calls, Read() and CountAll(), read the data and generate summary statistics for all variables in the data frame, plus histograms and bar charts as appropriate. Other functions provide for comprehensive summary statistics via pivot tables, a comprehensive regression analysis, analysis of variance and t-test, visualizations including the Violin/Box/Scatter plot for a numerical variable, bar chart, histogram, box plot, density curves, calibrated power curve, reading multiple data formats with the same function call, variable labels, color themes, and Trellis graphics. Also includes a confirmatory factor analysis of multiple indicator measurement models, pedagogical routines for data simulation such as for the Central Limit Theorem, generation and rendering of R markdown instructions for interpretative output, and interactive visualizations.

Title: Vectorised Nested if-else Statements Similar to CASE WHEN in
Functions for vectorised conditional recoding of variables. case_when()
enables you to vectorise multiple if and else statements (like 'CASE WHEN'
in 'SQL'). if_else() is a stricter and more predictable
version of ifelse() in 'base' that preserves attributes. These functions are
forked from 'dplyr' with all package dependencies removed and behave

Description: Functions for vectorised conditional recoding of
variables. case_when() enables you to vectorise multiple if and else
statements (like 'CASE WHEN' in 'SQL'). if_else() is a stricter and
more predictable version of ifelse() in 'base' that preserves
attributes. These functions are forked from 'dplyr' with all package
dependencies removed and behave identically to the originals.
Author: Stefan Fleck [aut, cre] (<https://orcid.org/0000-0003-3344-9851>),

Title: A package for LEarning STATistics
Description: This package contains some simple objects and functions to do
statistics using linear models and a Bayesian framework.