shapiro_normality_test

This function performs the Shapiro-Wilk test if the sample size is between 3 and 5000. Otherwise, it performs the Anderson-Darling test.

Summarizing data frames by calculating various statistical measures, including measures of central tendency, dispersion, skewness(), kurtosis(), and normality tests. The package leverages the 'moments' package for calculating statistical moments and related measures, the 'dplyr' package for data manipulation, and the 'nortest' package for normality testing. 'DataSum' includes functions such as getmode() for finding the mode(s) of a data vector, shapiro_normality_test() for performing the Shapiro-Wilk test (Shapiro & Wilk 1965 <doi:10.1093/biomet/52.3-4.591>) (or the Anderson-Darling test when the data length is outside the valid range for the Shapiro-Wilk test) (Stephens 1974 <doi:10.1080/01621459.1974.10480196>), Datum() for generating a comprehensive summary of a data vector with various statistics (including data type, sample size, mean, mode, median, variance, standard deviation, maximum, minimum, range, skewness(), kurtosis(), and normality test result) (Joanes & Gill 1998 <doi:10.1111/1467-9884.00122>), and DataSumm() for applying the Datum() function to each column of a data frame. Emphasizing the importance of normality testing, the package provides robust tools to validate whether data follows a normal distribution, a fundamental assumption in many statistical analyses and models.

Uzair Javid Khan

DataSum

Comprehensive Data Summarization for Statistical Analysis

Immad Ahmad Shah

Sukhdev Mishra

shapiro_normality_test function

<dl><dt>data</dt>
<dd>A numeric vector.</dd></dl>

Arguments

Perform Normality Test — shapiro_normality_test

<dl>

<dt>data</dt>
<dd>A numeric vector.</dd>

</dl>

shapiro_normality_test: Perform Normality Test

Description

Usage

Value

Arguments

Examples