Research Topics:

Quantitative Research | Statistical Analysis

Content Type:

Glossary

Blocking Factor Definition

The relevant external variable that is used to group (or block) experimental units into groups so that the experimental group and the control group are matched.

In market research, blocking factor is a statistical technique used in experimental design and analysis of variance, or ANOVA, to maintain the quality of market research. This method involves categorizing data into groups based on certain criteria, known as blocks, that are used to control for sources of variability that are not of primary interest. Blocks diminish the impact of the effects of irrelevant factors that could bias or noise into your results. With the blocks in place, researchers can focus on the impacts they are investigating. Properly implemented blocking factors enhance precision of experiments and contribute to the credibility of research outcomes.

Who relies on blocking factors?

Blocking factors are particularly useful to marketing researchers, statisticians and analysts when conducting experiments or studies that involve multiple variables or factors that could potentially introduce unwanted variability. By using blocking factors, researchers can isolate the effects of their primary variables of interest while accounting for the influence of other variables that might impact the results.

Why should I care about blocking factors?

By incorporating blocking factors, marketing researchers, statisticians and analysts can collect more reliable insights by reducing the impact of confounding variables. This action leads to more accurate interpretations of the relationships between variables. Without addressing blocking factors, outcomes may be skewed and can lead to incorrect conclusions.