Data Bank for Statistical Analysis and Visualization

Contains data organized by topics: categorical data, regression model, means comparisons, independent and repeated measures ANOVA, mixed ANOVA and ANCOVA. The package code is under GPL-2; the data sets are covered by the terms in the 'LICENSE.note' file (the author's data sets under CC0 1.0, and the 'heartdisease' data under CC BY 4.0, see the 'heartdisease' help page).

datarium: Data bank for statistical analyses and visualization

Contains 23 curated data sets for teaching classical statistical inference in R. Each data set is paired with the analysis it is designed to teach — one data set per test. The same map is available in R via ?datarium. Each analysis below links to its worked tutorial on Datanovia.

Comparing means

Analysis of variance (ANOVA)

Categorical data and proportions

Regression

Time series

Helper functions

The two data sets (Titanic and housetasks) are frequency/contingency table. We’ll create our demo data sets by recovering the original data from Titanic and housetasks tables.

To do so, first copy and paste the following helper function:

counts_to_cases <- function(x, countcol = "Freq") {
    if(!inherits(x, "table")) x <- as.table(as.matrix(x))
      x <- as.data.frame(x)
    # Get the row indices to pull from x
    idx <- rep.int(seq_len(nrow(x)), x[[countcol]])
    # Drop count column
    x[[countcol]] <- NULL
    # Get the rows from x
    x <- x[idx, ]
    rownames(x) <- 1:nrow(x)
    x
}

Then, recover the original data as follow:

# Load the data
data("Titanic")
data("housetasks", package = "factoextra")

# Recover the original raw data
titanic.raw <- counts_to_cases(Titanic)
housetasks.raw <- counts_to_cases(housetasks)