(14) Analyzing Evaluation Data in Excel
Session Number: 14
Track: Professional Development Workshops
Session Type: Professional Development Workshops
Workshop Lead Presenter: Ann K. Emery [Data Visualization Specialist - Independent consultant]
Time: Nov 10, 2015 (09:00 AM - 04:00 PM)
Audience Level: Beginner, Intermediate
Learning Outcomes: • Navigate the entire data analysis process from start to finish
• Import and merge datasets together (vlookup, hlookup, and text to columns)
• Organize spreadsheets for maximum efficiency (data management best practices, freezing panes, sheets, sorting, filtering, and Excel Tables)
• Clean data prior to analysis (checking for missing data, removing duplicate ID numbers, and recoding and transforming one variable into another)
• Explore preliminary patterns (spark lines and spark bars, data bars, and automatic color-coding through conditional formatting);
• Run descriptive statistics (measures of central tendency, measures of dispersion, skew / kurtosis, quartiles, and frequency analyses)
• Run inferential statistics (independent and dependent means t-tests, chi-square, and plug-ins)
• Create and navigate pivot tables for near-instant analyses
Facilitation Experience: I have been analyzing research and evaluation data for a decade. Major data analysis-related clients have included the State Department, Department of Education, Head Start agencies, the National Institute on Drug Abuse, the JPB Foundation, the Center for Community Change, dozens of school districts, and dozens of local nonprofits.
Through these experiences, I have mastered a number of statistical software programs and databases (primary programs include Access, SAS, SPSS, Excel, and Efforts-to-Outcomes). An underlying takeaway message in my data analysis workshops is that data analysis is a multi-stage critical thinking process, and that successful analysis relies more on your evaluation questions and innate curiosity than on specific software programs. During workshops we often discuss the pros and cons of each software program, as well as which datasets are best suited to each of the software programs.
Data analysis work is proprietary, but lessons learned have been adapted and shared in my YouTube channel: www.youtube.com/annkemery.
I wrote about the multi-stage data analysis process at “Top 10 Secrets of a Nonprofit Data Nerd,” available at http://www.bethkanter.org/excel-data-nerd/. My article is one of the most-read posts of all time on Beth Kanter’s blog.
Ever feel like you're swimming upstream in data? Need to make sense of spreadsheets, but not sure where to start? Have a gut feeling that you're not getting the most out of common software programs like Microsoft Excel? Ann K. Emery will guide you through the entire data analysis process including importing and merging multiple datasets together to build a master dataset that can be used for analyses; assessing missing data and removing duplicate entries; recoding and transforming variables; exploring preliminary patterns through spark lines and conditional formatting; running descriptive statistics and frequencies; performing inferential statistics (and guidance for using Excel plug-ins or other software programs for these analyses); saving time and energy with pivot tables; and dealing with names, dates, and text fields. This workshop utilizes a variety of sample spreadsheets, such as survey data, outcome data, demographic data, and more. This workshop is highly interactive; laptops required.
For questions or concerns about your event registration, please contact firstname.lastname@example.org or 202-367-1173.
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Cancellation Policy: Refunds less a $50 fee will be granted for requests received in writing prior to 11:59 PM EDT October 6, 2015. Email cancellation requests to firstname.lastname@example.org. Fax request to (202) 367-2173. All refunds are processed after the meeting. After October 6, 2015 all sales are final.