What Is a Confidence Level?
A confidence level is the standard that determines how strictly differences between groups are evaluated in analysis results.
The higher the confidence level, the larger a difference must be before it is flagged as statistically significant. The lower the confidence level, the more relaxed the standard for identifying differences.
Why Should You Set a Confidence Level?
1️⃣ Determine whether differences between groups are statistically meaningful.
When analyzing survey results, it's important not just to look at differences in response rates, but also to assess whether those differences occurred by chance or represent a genuinely meaningful difference. Setting a confidence level lets you interpret differences between groups more objectively based on this standard.
2️⃣ Interpret results at the level of rigor that fits your analysis goals.
The level of rigor required may vary depending on the purpose of the research. For example, marketing research aimed at quickly gathering insights may use a relatively relaxed standard, while analysis that requires precise statistical testing may call for a stricter one. Setting a confidence level lets you interpret results according to the standard that best fits your analysis goals.
How to Set the Confidence Level
📌 The confidence level setting is available on all plans.
Step 1. In the right sidebar of the Analytics screen, select the confidence level you want (80%, 90%, or 95%).
💡 Usage tip | An 80% confidence level — appropriate for general marketing research — is provided as the default. If your analysis requires a stricter statistical standard, you can adjust it to 90% or 95%.
Step 2. When you change the confidence level, the updated standard is applied to your analysis results.
Results tab: The sampling error information changes based on the selected confidence level.
Cross-tab tab / Report tab: The statistical test results displayed through color coding in the cross-tab table will change.
Frequently Asked Questions
Q. When should I use 80%, 90%, or 95%?
A. You can choose a confidence level based on your analysis goals and the level of rigor required.
80% confidence level: Commonly used for general marketing research or when the goal is to quickly identify insights. Dataspace provides this as the default value.
90% confidence level: Can be used when you want to analyze with a relatively higher degree of accuracy.
95% confidence level: Primarily used for academic research or when very rigorous statistical testing is required.
💡 As the confidence level increases, the standard for determining whether a difference is statistically significant becomes more stringent.
Q. What is the difference between confidence level and sampling error?
A. Both confidence level and sampling error are indicators that describe the reliability of statistical results, but they differ in meaning and role.
Confidence level: The standard for determining whether differences between groups are statistically meaningful.
Sampling error: The range that shows how much the survey results may differ from the actual population.
For example, a confidence level of 95% with a sampling error of ±3% means that if the same survey were repeated multiple times, the actual value would fall within ±3% of the result 95% of the time.
Have you got a good understanding?
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