Quantitative Research and Evaluation Methods
Quantitative Research Course Description
Are you an evaluator, researcher, or social scientist who is looking to learn more about the basics of quantitative methods? These methods are commonly used when quantitative data and information can be incorporated to answer various questions about a program’s impact and fidelity of implementation. We will explore various quantitative methods including quasi-experimental and experimental designs, introduce some of the analytic techniques used in these designs, highlight issues related to the use of measurement (such as surveys) and databases, and present multiple examples of how this knowledge can be used in the real-world.
This course is delivered in four interactive modules. Read more about each of the modules below. Classes will take place online via Adobe Connect or Zoom. Certificates of completion will be provided at the end of the course to all participants who have successfully completed the modules.
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Module 1: Experimental & Quasi-Experimental Designs Part I
Module 1 builds a foundation for understanding various quantitative research designs, including random and non-random designs, and the conditions where they can be optimally used. We will also go through various validity issues related to each design option and discuss ethical considerations to keep in mind when using these approaches.
Module 2: Experimental & Quasi-Experimental Designs Part II
Module 2 builds on the first session, providing examples of how various experimental and quasi-experimental designs can be used in evaluation, with a focus on the practical aspects of implementing these designs in the real world. By studying these examples, participants will have the opportunity to learn about the benefits and challenges associated with various designs.
Module 3: Measurement & Databases
Module 3 will focus on the various types of data and measures that can be used in quantitative designs. The module will cover issues related to sampling, measurement design, operationalizing constructs, and using existing measures and databases to answer various evaluation questions.
Module 4: Introduction to Analytic Techniques
The final module will introduce participants to some of the commonly used statistical techniques used in the analysis of quantitative data, including descriptive statistics and inferential statistics (such as regression, t-test, and Analysis of Variance (ANOVA)). This introduction will be on the conceptual level, but will offer a perspective on how to approach the analysis process. The instructor will share resources on analytic techniques, analysis software (free and paid), and where to access more advanced topics for those who wish to pursue additional self-study.
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