Reviewing Data

Reviewing Data

Now that you have analyzed your data, you will need to review and interpret the results. This process enables you to know what the results mean and prepares you for communicating your results to others. This process can be broken down into four steps:

  • Description and Analysis
  • Interpretation
  • Judgment
  • Recommendations

 

Description and Analysis

This step involves looking at the results of the data analysis and organizing the results so that the audience/stakeholder understands the data and can detect patterns.  This data analysis should be described in a simple straightforward fashion no matter how complex the data or analysis.

Aiming for simplicity does not mean that only one perspective can be presented. Rather, presenting different perspectives on the data can help create a balanced analysis.

Description and Analysis

To help stakeholders or your audience understand the results, presenting clear definitions of key terms and concepts is essential. Let’s say your evaluation assessed a youth development program. When describing data about the youth in this program, the specific ages of the youth must be clearly defined since not all cultures define “youth” the same way.

Along with clear definitions of key terms, communicating results also requires making careful comparisons.

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A percentage standing alone also doesn’t tell us very much. Describing results often involves a comparison, like a comparison between youth that do and do not participate in programs. The comparisons you choose should be carefully selected so that they add meaning to the results. Selecting careful comparisons means using appropriate information or data to appropriately illustrate your results. Options for careful comparisons include

  • Outcomes of similar programs or evaluations
  • Outcomes from the same program from other years
  • The goals of the program
  • The participants' goals for their involvement

 

 

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