Randomized Block Design is a statistical method used in experiments to reduce the impact of variability among experimental units. In this design, subjects are divided into groups, or "blocks," based on a specific characteristic, such as age or gender. Each block is then randomly assigned to different treatment conditions, ensuring that each treatment is tested across all blocks. This approach helps to control for confounding variables, making it easier to detect the true effect of the treatments being studied. By accounting for variability within blocks, researchers can obtain more reliable and valid results, leading to better conclusions about the effectiveness of the treatments.