Block designs are a type of experimental design used in statistics to control for variability among experimental units. They involve grouping similar units into blocks, allowing researchers to compare treatments more effectively. Each treatment is applied within each block, helping to reduce the impact of confounding variables. These designs are particularly useful in agricultural experiments, where factors like soil type or location can affect results. By using block designs, researchers can ensure that comparisons between treatments are more reliable, leading to clearer conclusions about the effects of different treatments on outcomes.