Evaluation Data Analysis
Data analysis for evaluation is about looking for and investigating patterns through either quantitative (numerical) or qualitative (textual and/or visual) data. If using both kinds of data, considerations must be given to how these methods will be combined to enrich, examine, explain, and triangulate findings.
Analysis Process
What is it? Data analysis is the process of cleaning, organizing, and transforming data, so that you can find patterns within the data to discover useful information for decision-making. In order to draw helpful and insightful conclusions, your data must be grounded in established evaluation questions that guide your evaluation design and the methods used. Data findings are only as good as the analysis conducted, and the analysis is only as good as the data collected. This is why following data protocols at every step is important.
There are different analytic approaches and protocols for evaluations using quantitative methods, qualitative methods, or mixed methods, depending on the evaluation objectives and the data collected. Our consultants can help you determine which types of analysis are best for your evaluation or coach you through analyzing your data appropriately.
How can we help you?
- Identify the data and analysis type needed based on evaluation question(s)
- Develop data collection methodology to ensure solid analysis and findings
- Set up analysis plan and protocols
- Set up database plan and protocols
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Read MoreFAQ About Analysis Process
The process is similar to how research analysis would be conducted, in that an evaluation and coordinating analysis plan would be developed early on in project planning, both tied to key analysis questions that drive the methods used.
The major advantages of longitudinal analysis are that you can assess change or show clear patterns, as there are multiple time points of data collection. The major disadvantages are that this type of study takes longer to do, is more expensive, and is more limited in terms of breadth of experience.
If future reporting is easy and quicker due to development of standardized data processing and presentation elements.
Data from document review can be inaccurate, incomplete, biased, disorganized, or irrelevant, therefore, it can also be time consuming to compile, organize, and analyze a large volume of documents.
Semi-structured interviewing is the most common type, which includes an interview guide with pre-determined open-ended questions, but also the flexibility of allowing spontaenuous follow-up questions and probing to yield in-depth data.
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