Learn how to quickly explore your data and find initial patterns.
Learn how to use conditional formatting to automatically color-code specific response options in a satisfaction survey.
Learn to automatically color-code cells and scan for patterns in your dataset using top/bottom rules.
Color-code scores and then calculate r to measure the correlation between pretest and posttest scores.
The ultimate purpose of data analysis and evaluation is to share findings with other leaders at your organization and use that information to make adjustments and improvements. You don’t need a lot of data, and the analyses don’t have to be complicated or time-consuming. Sometimes the simplest data are the most useful. Here’s an example where I created data bars — miniature within-cell bar charts — to quickly compare each youth’s pretest score and posttest score.