Explore data related to the Doctor Who TV series.

Data screening is an important first step of any statistical
    analysis. 'dataReporter' auto generates a customizable data report with a thorough
    summary of the checks and the results that a human can use to identify possible
    errors. It provides an extendable suite of test for common potential
    errors in a dataset. See Petersen AH, Ekstrøm CT (2019). "dataMaid: Your Assistant for Documenting Supervised Data Quality Screening in R." _Journal of Statistical Software_, *90*(6), 1-38 <doi:10.18637/jss.v090.i06> for more information.

Quality control and formatting tools developed for the Copernicus Data Rescue Service. The package includes functions to handle the Station Exchange Format (SEF), various statistical tests for climate data at daily and sub-daily resolution, as well as functions to plot the data. For more information and documentation see <https://datarescue.climate.copernicus.eu/st_data-quality-control>.

Collection of functions to help retrieve U.S. Geological Survey
    and U.S. Environmental Protection Agency water quality and
    hydrology data from web services.

Contains data organized by topics: categorical data, regression model, 
            means comparisons, independent and repeated measures ANOVA, mixed ANOVA and ANCOVA.

For working with the 'DataRobot' predictive modeling platform's API <https://www.datarobot.com/>.

The Datasaurus Dozen is a set of datasets with the same
    summary statistics. They retain the same summary statistics despite
    having radically different distributions.  The datasets represent a
    larger and quirkier object lesson that is typically taught via
    Anscombe's Quartet (available in the 'datasets' package). Anscombe's
    Quartet contains four very different distributions with the same
    summary statistics and as such highlights the value of visualisation
    in understanding data, over and above summary statistics. As well as
    being an engaging variant on the Quartet, the data is generated in a
    novel way. The simulated annealing process used to derive datasets
    from the original Datasaurus is detailed in "Same Stats, Different
    Graphs: Generating Datasets with Varied Appearance and Identical
    Statistics through Simulated Annealing" <doi:10.1145/3025453.3025912>.