Guides: Research Methodology: Data Analysis

Data Analysis Overview

Data Analysis and Presentation Techniques that Apply to both Survey and Interview Research

Create a documentation of the data and the process of data collection.
Analyze the data rather than just describing it - use it to tell a story that focuses on answering the research question.
Use charts or tables to help the reader understand the data and then highlight the most interesting findings.
Don’t get bogged down in the detail - tell the reader about the main themes as they relate to the research question, rather than reporting everything that survey respondents or interviewees said.
State that ‘most people said …’ or ‘few people felt …’ rather than giving the number of people who said a particular thing.
Use brief quotes where these illustrate a particular point really well.
Respect confidentiality - you could attribute a quote to 'a faculty member', ‘a student’, or 'a customer' rather than ‘Dr. Nicholls.'

Sample Tools for Analyzing Survey Data

Excel
R (open source)
SAS
SPSS
Stata
DataCracker (free up to 100 responses per survey)
SurveyMonkey (free up to 100 responses per survey)

Sample Tools for Analyzing Interview Data

AQUAD (open source)
R (open source)
NVivo
TAMS
MAXQDA
Dedoose
ATLAS.ti

Data Science @ WPI

Data Science Faculty @ WPI
The Data Science Program prepares WPI students with the skills to understand, apply, and develop models, algorithms and statistical techniques to gather datasets, draw new insights from that data, and formulate appropriate action plans.

With its long history of research in big data management, artificial intelligence, statistics, and visual analytics, WPI is one of a handful of universities ready to prepare graduates for the challenges of this rapidly expanding field. This interdisciplinary program brings together a trifecta of faculty mentors from computer science, mathematics, and business. Combined with our community of student scholars from all over the world, we have a team of visionary leaders, scholars, and teachers prepared to contribute important insights that will change the way we live, how we work, and our interaction with the world around us. Check out their faculty to ask for expert assistance and forge partnerships

Cleaning and Scrubbing Data

Often you will need to reformat or clean the text or data you collect, for easier use in analytical tools highlighted in the Digital Scholarship LibGuide.

Be in touch with a Research Librarian or ARC experts about more information related to file conversion, manually structuring with Word and Excel (help with regular expressions), and/or correcting or standardizing text.

Academic Research Computing @ WPI

Academic Research Computing (ARC)
The Academic and Research Computing (ARC) team supports WPI faculty and student researchers by providing essential resources, services, and expertise.
ARC maintains state-of-the-art equipment and facilities including a robust computing infrastructure, fully equipped laboratories and facilities, and up-to-date scientific and engineering software applications (SESA). Our staff members work across campus to provide system administration, data management, and training and consulting for a variety of requests.

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Digital Scholarship
by Kate Boylan Last Updated Mar 31, 2025 140 views this year