Research Terms Explained

In this month’s Infosurv Infobit we’ll explain a few important research concepts by defining some commonly used terms in the market research industry.

To learn more about how these various concepts “fit together” in an online survey, please visit us at

Statistical Error

Statistical error is a measure of how accurately the responses of a survey sample reflect that of the population overall. For example, if statistical error is +/- 3% at the 95% confidence level, we can say with 95% confidence that our sample’s sentiments reflect that over the overall population within +/- 3%.

Bias Reduction

Bias reduction is achieved by avoiding leading questions, which gently or even subconsciously encourage respondents to answer in a certain way. Survey questions should be worded as neutrally as possible.

Response Rate

Response rate is the percentage of the target survey sample who responds to the survey. An industry-average response rate for employee survey is approximately 60%, though Infosurv regularly achieves response rates closer to 85-90%.

Independent & Dependent Variables

Dependent variables are those that management is hoping to positively affect, whereas independent variables are those that influence the dependent variables.

Branching Logic

Branching logic controls which survey questions are show to which respondents. For example, some questions may only be shown to employees in a certain department, or who are dissatisfied in a certain area.

Verbatim Comments

Infosurv recommends that every employee or customer survey contain at least 1-2 open-ended or verbatim comment sections. Verbatim data is much richer and more meaningful, though it requires more resources to properly analyze.

Normative Data

Normative data allows an organization to understand where they stand in comparison with other groups. Without this comparison you may waste resources fixing issues that simply reflect prevailing views of employees in general, and missing an opportunity to address the real areas in which your organization lags behind others.