From Surveys to Solutions: Why Statistical Thinking Matters
Introduction
Each year, National Statistics Day highlights the vital role that data and statistical reasoning play in research, planning, and decision-making across all disciplines. For the Technology Solutions team, statistics are not just numbers—they’re essential tools for understanding the campus community’s experiences and improving the services that support teaching, learning, and work at UIC.
Using Statistics to Understand Campus Feedback
Within Technology Solutions, the Marketing and Communications Group uses statistical methods to explore and analyze data from two key sources: our periodic campus-wide general surveys and our ongoing helpdesk surveys. These surveys collect valuable feedback from faculty and staff about the range of IT services offered across campus—from email and network support to classroom technology and account management.
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Predictive statistics are critical to formulating fair and balanced interpretations of survey results. Statistical tests and modeling provide universally agreed upon, standardized methods and decision rules to assess the relative meaningfulness of the difference—or concordance—between numbers.
| Statistical Software and Support Analyst
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In other words, statistics allow us to move beyond intuition or first impressions when interpreting data. They help determine whether observed differences in survey responses represent meaningful trends or are simply due to normal variation.
A Real-World Example
Consider this table, which summarizes the number of faculty and staff survey submissions for 12 Technology Solutions services over three academic years. At first glance, the table shows that average survey submissions declined from Year 2 to Year 3, and again from Year 3 to Year 4. But is that decrease statistically meaningful—or could it simply reflect ordinary variation in participation?
Statistical Software and Support Analyst Scott Young points out that without statistical testing, it’s easy to over-interpret such changes. “If someone claimed that participation was in ‘steep decline,’ readers with a background in data analysis would immediately ask: how do you define ‘steep’? How large must a difference be before it’s considered major or minor? Statistics provide the tools to quantify those differences objectively,” he says.
Why Objectivity Matters
Without statistical tests—such as t-tests, correlations, or regression models—interpretations risk being subjective. What one person calls a “major decline” another might consider negligible. Statistical methods help establish thresholds for what counts as meaningful, providing a shared language of evidence and reducing ambiguity.
This principle applies far beyond survey data. In fields such as clinical research, statisticians help design studies where the size and balance of experimental and control groups directly affect the precision of results. A statistician might recommend adjusting sample sizes or “tightening filters” in data to ensure fair comparisons—decisions that determine whether findings are reliable or misleading.
Turning Data Into Insight
For Technology Solutions, applying statistical rigor to survey analysis ensures that interpretations of campus feedback are fair, transparent, and actionable. It helps identify genuine shifts in user experience, guides service improvement efforts, and supports data-informed decision-making across the university.
“Statistics give structure and meaning to data. They help us distinguish between what’s significant and what’s just noise—so that we can make smarter, more balanced decisions for the UIC community,” Young says.