The goal of this app is to provide an interactive interface to help learn and teach basic quantitative variables univariate and bivariate analysis and visualization.

You can display basic statistics and visualizations, you can then play around with parameters, zoom, pan, drag data points, and everything should be updated dynamically with transitions.

Data can be manually typed, randomly generated from several distributions, or you can load a simple included dataset. Note that when a dataset is loaded, you won't be able to drag the points (as you shouldn't be able to do that in a real analysis).

Title | Description | Note | Source |
---|---|---|---|

Life expectancy by country | Life expectancy at birth, by country, in 2014 | World bank | |

Mother age at child birth | Sample of 2000 mother ages at child birth, in France, in 2015. Only ages from 18 to 45 (included) are taken into account. | An example of integer-only quantitative variable, following a slightly skewed normal distribution. | Insee |

Departments population | Population of each french department in 2013 | Wikipedia | |

Departments population density | Population density of each french department (in people per kmĀ²) in 2013 | An example of the influence of outliers on statistics and visualization. | Wikipedia |

!Kung people heights | Heights (in cm) from partial census data for the Dobe area !Kung San, compiled from interviews conducted by Nancy Howell in the late 1960s. | A bimodal dataset due to men and women heights having different distributions. | Statistical rethinking book dataset |

Title | Description | Note | Source |
---|---|---|---|

Life expectancy vs GDP per capita | European countries, 2007 | Gapminder R package | |

Life expectancy vs GDP per capita | World countries, 2007 | Example of non linear relationship | Gapminder R package |

928 children height and their mid-parents heights | Francis Galton, 1886 | Historical dataset, used to show the concept of regression towards the mean. | Galton R package |

- The source code of this app is freely available on Github under an MIT license.
- Interface powered by Bootstrap
- Graphics powered by D3.js
- Regression calculations by simple-statistics