Keng(庚)

The Keng package is named after Loo-Keng Hua, who made great achievements in mathematics mainly through self-study. Loo-Keng Hua encouraged novices to show their axe skills at the gate of Ban’s house, so the Keng package comes. In addition, Keng is the abbreviation of “Knock Errors off Nice Guesses.”

The Keng package aims to automate the computations Qingyao repeat in his psychological research and teaching. Hope the functions and data gathered in this package help to ease your life.

Installation

You can install the development version of Keng from GitHub with:

install.packages("pak")
pak::pkg_install("qyaozh/Keng")

Load

Before using the Keng package, load it using the library() function.

library(Keng)

List of contents

Here is a list of the functions and data gathered in the Keng package. Their usages are detailed in the documentation.

Pearson’s r

cut_r() give you the cut-off values of Pearson’s r at the significance levels of p = 0.1, 0.05, 0.01, 0.001 when the sample size n is known.

test_r() tests the significance of r using t-test when r and n is known.

The linear model

compare_lm() compare lm()’s fitted outputs using PRE and R².