Between-group

Referring to comparisons or analyses conducted *across* different, pre-existing groups or conditions in a study. This contrasts with within-group designs, where the same subjects are measured under multiple conditions. between-group designs aim to determine if there are statistically significant differences in a measured outcome *between* these distinct groups. The core focus is examining the variation that exists *between* the groups, considering the factors that might explain these differences. Researchers employ statistical methods like t-tests, ANOVAs, and chi-square tests to analyze the data derived from such designs.

Between-group meaning with examples

• A pharmaceutical company conducted a study comparing the effectiveness of a new drug (treatment group) against a placebo (control group) for reducing blood pressure. The study used a between-group design, assigning participants randomly to either the treatment or the control group. Data from the two groups were then analyzed to see if there was a significant difference between their post-treatment blood pressure levels.
• In an educational setting, researchers investigated the impact of two different teaching methods (Method A and Method B) on students' test scores. Students were randomly assigned to either Method A or Method B, forming two distinct between-group. The researchers used the average scores of each group to compare each method's effectiveness, revealing which method had better results.
• A marketing team wants to measure the effect of an advertising campaign on sales numbers. They design a between-group design in which one location receives the ad, and another, similar location does not. The company would compare the locations, between-group data analysis that measures whether the ad has had any tangible impact on sales. This analysis focuses on comparing sales figures.
• An experiment aimed to measure the effects of different types of fertilizer on crop yield. Several fields were used, and different fertilizers were randomly assigned to each field (group). After a certain period, the amount of harvest per group was measured and compared. This between-group study was completed by using statistical analysis to determine if the differences in crop yield between the fertilizer groups are statistically significant.