Significant Testing

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What is Significance Testing?

Significance testing is one of the most widely used terms by researchers, and it answers a simple question: “are the differences we see between groups beyond chance?” When comparing groups in a survey sample, it is important to understand whether the differences between these groups are “significantly different” or within the normal margin of error for the sample.

There are many forms of significance testing that you can use, including, T Testing, Analysis of Variance (ANOVA), Chi-Square Testing, Z Score Testing, and many more. Finding the right significance test for your analysis depends on multiple factors, including the type of independent variable, the type of dependent variable, your sample size, and the number of groups you need to compare.

When to use Significance Testing?

Utilize significant testing when you want to gain more confidence about the differences between two audiences, products, or outcomes.

For example, suppose you are tasked with testing four potential ice-cream flavor concepts. In order to choose the best flavors to bring to market, you decide to survey consumers about their likelihood to purchase each flavor.

Significance testing among the four concepts will tell you whether the difference in purchase intent between each of the flavors is significant, or within a margin of error.

Why Use Significance Testing?

Discover Significant Differences Between Your Concepts

Learn whether consumer preferences on your product, ad, or messaging concepts are significantly different across each concept, or if the differences you see are simply chance.

Better Understand Your Audience

Analyze respondent data to uncover significant differences in consumer preferences, purchase intent, and price sensitivity across your market segments.

Improve Decision Making

Determine whether the differences between your variables are significant, or due to chance, to make more efficient business decisions.

How to Apply

Significance Testing

Applying significance testing in SightX is simple! Within the ANALYZE section of the platform, select the “Signifigence Testing” tab. Just choose the variables you need to compare, and SightX will automatically give you a significance level and data visualizations to match.