Area Chart Figure 1: Area chart Use it to… * Display over time (or any other dimension): * How a set of data adds up to a whole (cumulated totals) * Which part of the whole each element represents Variants * Percentage: The sum always represents 100% (relative scale) * Cumulative: The sum can vary according to the elements (absolute scale) Column/Bar Chart Use it to… * Present few data over a nominal (e. g. countries, testing conditions, … or interval scale (e. g. time); useful for comparisons of data Do not Use it for… * Comparisons: Better use one-dimensional scatterplots, because these are not dominated by bars or columns. * Larger data sets: Use line charts. Selecting Bars or Columns * Use analogy as a selection criterion, if applicable; when in doubt, use columns * Use a horizontal bar chart if the labels are too long to fit under the columns Variants Multiple Column/Bar Chart: Use it to present data rows for several variables * Side-by-Side Chart: Use it to (1) show contrasting trends between levels of an independent variable, (2) if comparisons between individual pairs of values are most important; do not use for more than two independent variables | | | Figure 2: Multiple column chart (left), side-by-side chart (right) Segmented Column/Bar Chart Other Names: Divided or stacked column/bar chart

Figure 3: Segmented column chart (relative values) Use it to… * Present a part-whole relation over time (with accurate impression, see below) * Show proportional relationships over time * Display wholes which are levels on a nominal scale Segmented column/bar charts are more accurate than pie chart, because distances can be more accurately estimated than areas. Frequency Polygon, Histograms Figure 4: Histogram as frequency distribution Variants Polygon: Connects data points through straight lines or higher order graphs * Histogram: Columns/bars touch; useful for larger sets of data points, typically used for frequency distributions * Staircase Chart: Displays only the silhouette of the histogram; useful for even larger sets of data points, typically used for frequency distributions * Step chart: Use it to illustrate trends among more than two members of nominal or ordinal scales; do not use it for two or more variables or levels of a single variable (hard to read) * Pyramid histogram: Two mirror histograms; use it for comparisons

Line Chart Figure 5: Line chart Use it… * To display long data rows * To interpolate between data points * To extrapolate beyond known data values (forecast) * To compare different graphs * To find and compare trends (changes over time) * To recognize correlations and covariations between variables * If the X axis requires an interval scale * To display interactions over two levels on the X axis * When convention defines meaningful patterns (e. g. a zigzag line) Line graphs may consist of line or curved segments: Lines: Use straight lines to connect “real” data points * Curves: Use curves to represent functional relations between data points or to interpolate data Do not Use it… * If the X axis has non-numeric values Variants * Graph with double-logarithmic or half-logarithmic scale divisions * Graph with variance bars, stock charts (High/Low/Close) etc. Pie Chart Figure 6: Pie chart Use it to… * convey approximate proportional relationships (relative amounts) at a point in time * compare part of a whole at a given point in time Exploded: emphasize a small proportion of parts Do not Use it … * For exact comparisons of values, because estimating angles is difficult for people. * For rank data: Use column/bar charts in this case; use multiple column/bar charts for grouped data * If proportions vary greatly; do not use multiple pies to compare corresponding parts. Caution! * Pie charts cannot represent values beyond 100%. * Each pie chart is valid for one point in time only. * Pie charts are only suited to presenting quite a few percentage values. Angles are harder to estimate for people than distances; perspective pie charts are even harder to interpret. Scatterplot | | | Figure 7: One-dimensional scatterplot (left), two-dimensional scatterplot (right) Variants 1. One-dimensional scatterplot: Data point are drawn above a baseline (as in column/bar charts). Here the data points are not connected but remain isolated data points. 2. Two-dimensional scatter plot: Shows correlation between two data sets.

This chart type has two dependent variables: One is plotted along the X axis, the other along the Y axis; the independent variable is the intersection of both dependent variables, realized as a data point in the diagram. Use it to… * Show measurements over time (one-dimensional scatterplot) * Convey an overall impression of the relation between two variables (Two-dimensional scatterplot) Do not Use it for… * Determining and comparing trends, interpolation, extrapolation, recognition and comparison of change rates * More than one independent variable: Avoid illustrating more than one independent variable in a scatter plot A histogram typically shows the quantity of points that fall within various numeric ranges (or bins). * A bar chart uses bars to show frequencies or values for different categories. * A pie chart shows percentage values as a slice of a pie. * A line chart is a two-dimensional scatterplot of ordered observations where the observations are connected following their order. * A bubble chart is a two-dimensional scatterplot where a third variable is represented by the size of the points. A Polar area diagram, sometimes called a Coxcomb chart developed by Florence Nightingale is an enhanced form of pie chart. * A radar chart or “spider chart” is a two-dimensional chart of three or more quantitative variables represented on axes starting from the same point. * A waterfall chart also known as a “Walk” chart, is a special type of floating-column chart. * A Tree Map where the areas of the rectangles correspond to values. Other dimensions can be represented with colour or hue.