Visualize your 'Tidyverse' data analysis pipelines via the 
    'Tidy Data Tutor'(<https://tidydatatutor.com/>) web application.

Delta Method implementation to estimate standard errors with known 
    asymptotic properties within the 'tidyverse' workflow. The Delta Method is a
    statistical tool that approximates an estimator’s behaviour using a Taylor 
    Expansion. For a comprehensive explanation, please refer to Chapter 3 of van
    der Vaart (1998, ISBN: 9780511802256).

Cleans spectrophotometry data obtained from the Denovix instrument. The package also provides an option to normalize the data in order to compare the quality of the samples obtained.

To make it easy to generate random numbers based upon the underlying stats 
    distribution functions. All data is returned in a tidy and structured
    format making working with the data simple and straight forward. Given that the
    data is returned in a tidy 'tibble' it lends itself to working with the rest of the
    'tidyverse'.

Provides extended data frames, with a special data frame column which contains two indexes, with potentially a nesting structure, and support for tibbles and methods for 'dplyr'.

Utils for basic statistical experiments, that can be used for teaching 
    introductory statistics. Each experiment generates a tibble.
    Dice rolls and coin flips are simulated using sample().
    The properties of the dice can be changed, like the number of sides.
    A coin flip is simulated using a two sided dice.
    Experiments can be combined with the pipe-operator.

A tidy-style interface for applying differential privacy to data frames.
    Provides pipe-friendly functions to add calibrated noise, compute private statistics,
    and track privacy budgets using the epsilon-delta differential privacy framework.
    Implements the Laplace mechanism (Dwork et al. 2006 <doi:10.1007/11681878_14>) and
    the Gaussian mechanism for achieving differential privacy as described in Dwork and
    Roth (2014) <doi:10.1561/0400000042>.