Imputation in the context of catalysis refers to the process of estimating or inferring missing data points in experimental datasets. In catalytic studies, data imputation is essential as missing data can arise due to experimental errors, instrument limitations, or other unforeseen circumstances. Effective imputation ensures that the datasets are complete and reliable for further analysis.
