In the study of catalytic reactions, data can often be noisy due to experimental errors, fluctuations in reaction conditions, or other external factors. The moving average helps to filter out this noise, providing a clearer picture of the underlying trends. This is crucial for understanding the efficacy of a catalyst, optimizing reaction conditions, and ensuring reproducibility.
