Dana Wanzer, PhD, Assistant Professor of Psychology in Evaluation at the University of Wisconsin-Stout
You’ve collected your data… now what? This two-part eStudy will walk you through the steps for analyzing your quantitative evaluation data to prepare for reporting back to clients. In the first part, you will learn how to perform descriptive statistics to describe your data (e.g., frequencies, averages). In the second part, you will learn how to perform inferential statistics to use your sample data to make inferences about your population of interest (e.g., determine the correlation between two variables, examine group differences in an outcome). Note that we will not use any software in this course and focus more on conceptual understanding of the various descriptive and inferential statistics. Resources and guides on how to perform these analyses in Excel, SPSS, jamovi, and R will be provided.
- Understand the various measurement levels of quantitative data
- Analyze data using the appropriate descriptive statistics
- Distinguish descriptive statistics from inferential statistics
- Choose the appropriate inferential statistic
- Understand the basic process for performing inferential statistics
- Perform three basic inferential statistics (i.e., chi-square, correlation, independent t-test)
- Descriptive statistics (Wanzer, 2023)
- Inferential statistics (Wanzer, 2023)
- Links to the resources, which will include text, videos, and practice activities, will be provided closer to the workshop dates
This workshop is aligned to AEA’s Competencies and Guiding Principles as follows: This estudy on quantitative data analysis aligns primarily with the guiding principle of systematic inquiry and the competency of methodology.
Facilitation Experience: Dana aims to make statistics understandable, enjoyable, and practical for learners. She has taught statistics to undergraduate students, graduate students, and working professionals and has ample experience facilitating workshops on a variety of topics for the past six years. The workshop meetings will be very hands-on, applying what we learned in the homework done before each session.
Primary Audience (Who would benefit from this presentation and why?): Evaluators with limited experience analyzing quantitative (i.e., numbers) data are welcome. No previous experience with data analysis is required, although understanding some basics about evaluation designs (e.g., experimental, quasi-experimental, survey, between- and within-subjects), collecting quantitative data, spreadsheets, and algebra (e.g., calculating means, understanding basic mathematical symbols) will be helpful. You will need to be able to access Google Slides for the hands-on activities.
April 4, 2023 12:00 - 1:30 PM ET
April 11, 2023 12:00 - 1:30 PM ET
Once you purchase the eStudy you must register for each session. Recordings will be made available to registrants unable to attend sessions live. Recordings will be made available to all registrants for 90 days.