Larger data sets: use line charts. Selecting Bars or Columns ;k 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 * 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 I Figure 2: Multiple column chart (left), side-by-side chart (right) Segmented
Column/AR Chart Other Names: Divided or stacked column/bar chart Figure 3: Segmented column chart (relative values) * 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 * 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 Else 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) ;k To recognize correlations and cavitations between variables ;k If the X axis requires an interval scale ;k 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 to use it… K If the X axis has non-numeric values -k Graph with double-logarithmic or half-logarithmic scale divisions With variance bars, stock charts (High/LOW/Chose) etc. Pie Chart Figure 6: Pie chart * Graph * convey approximate proportional relationships (relative amounts) at a point * compare part of a whole at a given point in time 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
It proportions vary greatly; do not use column/bar charts tort grouped data multiple pies to compare corresponding parts, Caution! ;k Pie charts cannot represent values beyond 100%. * Each pie chart is valid for one point in time only, ;k 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. Scattered Figure 7: One-dimensional scattered (left), two-dimensional scattered (right) 1. One-dimensional scattered: Data point are drawn above a baseline (as in alumna/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-confessional scattered).
