Currently all courses are run live either in person or online (via Zoom), but we are working on some online courses. Check back here often for more, or subscribe to get updates via email.
Practical R
How many times have you or someone you know said, “I would love to learn R, but I just don’t have the time!” Or, “I want to learn R, but it seems so hard!” Many R courses spend a lot of time walking students through examples that don’t directly apply to their daily work. We will ensure that the tasks you engage in directly apply to your data management and basic statistical analysis needs.
In this course, you will get hands on experience working with R so you can walk away feeling confident using R in practical ways. In this class, you will learn how to import data sets from Excel, merge data files, and run basic statistical tests (e.g., compute means, run a t-test, run a correlation). Our goal is for you to feel comfortable with R so that you can get started with data analyses and data management right after completing our course.
This course can be tailored to your organization’s needs in terms of number of classes (we recommend six 2-hour sessions) and topics. We can even analyze your organization’s own data.
SPSS
Quick SPSS
The intro class is a 2-hour survey of what SPSS can do, and is designed to get you up and running in SPSS. We’ll cover loading data, using the syntax window, looking in the output window for results, how to run descriptive statistics, correlations, t-tests, and if there’s time, regressions or other topics. Great for beginners or as a refresher.
Advanced SPSS
Already know how to use SPSS, but need a little more help to get you to the next level? Gain insight into how to run analyses, manage data, and build codebooks. We will walk you through the various ways to conduct simple to complex statistical analyses, how to use custom data tables, and create user-friendly codebooks. With our aim of providing user-friendly and practical training, this course will leave you feeling excited to explore your data and answer your most burning research questions!
Rapid cycle evaluation
Many programs have clearly stated goals, but check on their progress annually because the data can only be obtained annually (e.g., standardized test scores), without using methods to assess smaller components of these goals that can better inform the project in real time. Think of a rapid evaluation as baby-steps toward reaching your program’s main goals. In this class, we will help you to identify the major goals of your program and break them down into smaller digestible bites. Within these smaller components of your program, where can you find room for improvement? Once you have identified areas that can be improved, identify the low-hanging fruit and work your way up the list! Working with that first small bite, what is something you and your team can commit to changing for 30 days? How will you measure the change? What will you do if there has or has not been an improvement?
This course will empower you to answer these questions and begin rapidly evaluating your program.