SummaryTowards efficient experiments.Under industrial conditions, where we encounter large random fluctuations, large numbers of observations, and a multiplicity of influencing factors, a proper analysis of the data on a statistical basis has become an essential part of our experimental techniques, which ultimately leads to more efficient methods of experimentation. This is illustrated by7practical examples.The first4examples deal with simple experiments for comparing two batches of raw materials when disturbing factors such as a time trend must be eliminated. The last3examples discuss more complex cases, namely a three‐factor experiment in the foundry, a latin square experiment in nylon spinning, and a five‐factor experiment of a mixed kind on gear‐noise testing.An attempt is made to explain in a simple form the relation between the statistical analysis of and the technical conclusions to be drawn from the result of a properly designed exper