# Quantitative visualizations

## Pie charts

A pie chart (or a circle graph) is a circular chart divided into sectors, illustrating numerical proportion. In a pie chart, the arc length of each sector (and consequently its central angle and area), is proportional to the quantity it represents. http://en.wikipedia.org/wiki/Pie_chart

## Histograms

A histogram is a graphical representation of the distribution of data. It is an estimate of the probability distribution of a continuous variable and was first introduced by Karl Pearson. A histogram is a representation of tabulated frequencies, shown as adjacent rectangles, erected over discrete intervals (bins), with an area equal to the frequency of the observations in the interval. The height of a rectangle is also equal to the frequency density of the interval, i.e., the frequency divided by the width of the interval. The total area of the histogram is equal to the number of data. http://en.wikipedia.org/wiki/Histogram

## Kernel density estimates

Kernel density estimation (KDE) is a non-parametric way to estimate the probability density function of a random variable. Kernel density estimation is a fundamental data smoothing problem where inferences about the population are made, based on a finite data sample. http://en.wikipedia.org/wiki/Kernel_density_estimation

A kernel density estimate provides a means of estimating and visualizing the probability distribution function of a random variable based on a random sample. In contrast to a histogram, a kernel density estimate provides a smooth estimate, via the effect of a smoothing parameter called the bandwidth, here denoted by h. With the correct choice of bandwidth, important features of the distribution can be seen; an incorrect choice will result in undersmoothing or oversmoothing and obscure those features. http://bl.ocks.org/jfirebaugh/900762

## Q–Q plot

Q–Q plot ("Q" stands for quantile) is a probability plot, which is a graphical method for comparing two probability distributions by plotting their quantiles against each other. First, the set of intervals for the quantiles are chosen. A point (x,y) on the plot corresponds to one of the quantiles of the second distribution (y-coordinate) plotted against the same quantile of the first distribution (x-coordinate). Thus the line is a parametric curve with the parameter which is the (number of the) interval for the quantile. http://en.wikipedia.org/wiki/Q%E2%80%93Q_plot

## Box plots

A box plot or boxplot is a convenient way of graphically depicting groups of numerical data through their quartiles. Box plots may also have lines extending vertically from the boxes (whiskers) indicating variability outside the upper and lower quartiles, hence the terms box-and-whisker plot and box-and-whisker diagram. Outliers may be plotted as individual points. http://en.wikipedia.org/wiki/Box_plot

## Bullet charts

A bullet graph is a variation of a bar graph developed by Stephen Few. Seemingly inspired by the traditional thermometer charts and progress bars found in many dashboards, the bullet graph serves as a replacement for dashboard gauges and meters. http://en.wikipedia.org/wiki/Bullet_graph