Visualizing Data

For your project you will use a Shiny app to construct the appropriate graph(s).

For common measured-response experimental designs, in which a continuous numeric dependent variable is analysed in relation to a categorical independent variable, the appropriate way to visualize the data is with a boxplot or stripchart.

For study designs in which the dependent variable is categorical, as in the food choice experiment, the appropriate way to visualize the frequency data (the tallies of the different food types chosen) is a bar graph.

When there is both a dependent and independent categorical variable in the study design, then one can use a grouped bar graph or a mosaic plot to visualize the data.

Creating Effective Graphs

Regardless of the type of graph used, the independent variable (i.e., temperature in our example) is always placed on the horizontal (or X) axis and the dependent variable (i.e., height after 14 days) appears on the vertical (or Y) axis. For bar graphs, the y-axis will have a label “frequency” (or “count”), as that is what was measured for the categorical dependent variable. All figures must have a number (and be numbered sequentially) and a detailed title (called a “figure heading”) that are placed below the figure. For more details consult the Biology Procedures and Guidelines document.