TOPIC

Influencing factors on data collection

MY PROGRESS

Pug Score

0%

Best Streak

0 in a row

Study Points

+0

Overview

Practice

Watch

Read

Quiz

Next Steps

Get Started

Get unlimited access to all videos, practice problems, and study tools.

Try Now
Unlimited practice
Full videos

Back to Menu

Topic Progress

Pug Score

0%

Videos Watched

0/0

Best Practice

No score

Read

Not viewed

Best Quiz

No attempts

Best Streak

0 in a row

Study Points

+0

Read

Factors That Can Bias Data Collection

A statistical study can be calculated correctly and still mislead if the data itself was collected in a biased way. Learn the four common sources of bias in data collection: sampling method, question wording, timing, and response bias, with an example of each.

Why data collection can go wrong before it starts

A statistical study can follow every calculation correctly and still produce a misleading answer, if the data itself was collected in a way that skews the results. Understanding the common sources of bias in data collection is the first line of defense — before any calculation happens.

Factors that can bias data collection Four common sources of bias: sampling method (who is asked), question wording (how it is asked), timing (when data is collected), and response bias (how people answer, including social pressure to answer a certain way). Sampling method Who gets asked? A non-random sample skews the results. Question wording Leading or loaded questions push people toward an answer. Timing When data is collected (day, season, event) can shift responses. Response bias People may not answer honestly, especially on sensitive topics.
Four common sources of bias to check before trusting collected data.

Sampling method

If the people or items sampled don't represent the full population, the results only describe the sample — not the group they were meant to represent. Surveying only people leaving a gym about exercise habits, for example, over-represents people who already exercise.

Question wording

A leading or loaded question nudges respondents toward a particular answer. "Don't you agree that X is a problem?" pulls differently than a neutral "What do you think about X?" — the wording itself becomes a source of bias, independent of who is asked.

Timing

When data is collected can shift the results, especially for anything tied to season, day of week, or a recent event. Measuring commute satisfaction right after a major traffic incident, for instance, captures an unusually negative moment rather than a typical one.

Response bias

Even with a good sample and neutral wording, people don't always answer honestly — especially on sensitive topics, where social pressure pushes answers toward what feels acceptable rather than what's true. This is part of a broader set of concerns studied in census and bias and good sampling methods.

Related lessons