Evaluation Implementation:
Wilder Research, 2012 — Glossary of commonly-used terms in sampling, data analysis, and interpretation.
Wilder Research, 2010 — PowerPoint presentation about organizing, analyzing, and interpreting your data, including an interpretation activity. From Wilder Research program evaluation workshop series held on November 12, 2010 at Wilder Center.
Wilder Research, 2010 — Tip sheet about organizing, analyzing, and interpreting your data.
Wilder Research, 2009 — Introduction to and tips for analyzing quantitative and qualitative data and drawing conclusions.
Wilder Research, 2009 — Describes steps to help make data entry more efficient, including step-by-step data entry instructions, and analyzing data, with a focus on quantitative data analysis.
Wilder Research, 2008 — Provides basic options for organizing and analyzing quantitative and qualitative data.
University of Wisconsin – Extension, 2003 — Outlines a basic approach for analyzing and interpreting narrative data – often referred to as content analysis. Assumes a basic level of knowledge about data analysis.
SAMHSA CSAP, 2003 — This e-learning tutorial will introduce statistical concepts and explain how evaluation results are used. Good evaluations are essential to effective programs and the future of your prevention program. The tutorial also describes special challenges in evaluating prevention programs.
SAMHSA CSAP, 2003 — This e-learning tutorial uses a case-study approach to demonstrate how to use evaluation data and how to work more effectively with your evaluator. If you are not familiar with evaluation, you should complete Evaluation 101 and 102 before beginning this tutorial.
International Monetary Fund, 2003 — Identifies quality-related features of governance of statistical systems, statistical processes, and statistical products. The DQAF provides a structure for assessing existing practices against best practices, including internationally accepted methodologies. Assumes a basic knowledge of the topic.
National Science Foundation, 2002 — Basic guide to evaluation for those who want to learn about what evaluation can do and how to do an evaluation. The report is divided into four major sections: evaluation and types of evaluation, the steps in doing an evaluation, an overview of quantitative and qualitative data collection methods, and strategies that address culturally responsive evaluation.
U.S. Environmental Protection Agency, 2000 — Describes seven steps to ensure proper scrutiny of secondary data. Assumes a basic knowledge of the topic.
W.K. Kellogg Foundation, 1998 — This often-cited resource provides a framework for thinking about evaluation and outlines a blueprint for designing and conducting evaluations, either independently or with the support of an external evaluator/consultant.
University of Wisconsin – Extension, 1996 — Presents common mathematical techniques that can be used to evaluate raw data, including: numerical counts or frequencies, percentages, measures of central tendency, and measure of variability. Assumes a basic level of knowledge about data analysis.
U.S. General Accounting Office, 1993 — This in-depth paper provides rationales for determining when questionnaires should be used to accomplish your objectives. It also describes how to plan, design, and use a questionnaire in conducting a population survey.
Westat, Inc., 1993 — Describes the "how and why" of program evaluation and outlines the steps involved, working from the premise that many useful evaluations can be conducted by program staff who may not have formal training in evaluation.
Child Welfare Information Gateway, No Date — Provides links to information and resources to help at various stages of the evaluation process. Topics include evaluating program outcomes, planning for evaluation, evaluation design, collecting and analyzing data, and using evaluation results.
American Evaluation Association, No Date — Website that features an extensive number of links to Internet resources in nearly 20 categories including evaluation blogs, discussion lists, data analysis software, and scientifically based evaluation methods.
Minnesota Department of Health, No Date — Explores how to understand and present data, including questions to ask about the data, and important considerations when reviewing data.