The phrase "a more robust dataset" is correct and usable in written English.
It can be used when discussing the quality or strength of a dataset, often in the context of research, data analysis, or machine learning.
Example: "To improve the accuracy of our model, we need to gather a more robust dataset that includes diverse samples."
Alternatives: "a stronger dataset" or "a more comprehensive dataset".
However, a larger number of farms would provide a more robust dataset to compare the nutrient conservation progress of farms to the nutrient reductions expected by regulatory entities.
The present study is a retrospective, descriptive study that examines whether open-source data can be used in conjunction with official data to create a more robust dataset on jail suicides.
Expanding upon the current data collection process would enable researchers to create a more robust dataset, enrich the overall quality of the variables collected, and allow for a more nuanced understanding of the correlates of jail suicide.
This study offers some benefits not found in other RNA-sequencing studies, including that we sequenced the RNA from a diverse group of different subjects and demonstrated trends across subject groups, and we enriched the RNA to remove many ribosomal and human RNAs to characterize a more robust dataset.
This pattern confirms the trend previously suggested by microarray analysis [ 24], and represents a more robust dataset from which to make such observations: unlike the previous experiment, which involved hybridizing non-human samples to a human-specific microarray, these qRT-PCR results are not confounded by sequence mismatches between sample and microarray chip.
However, these results have been criticised due to methodological constraints on collection of testes size data, and a smaller more robust dataset did not find this relationship [45].
By comparing the predictions the EPA made with this more robust dataset, as well as with actual reported violations, Alfredo's team tried to see how well the agency was able predict the number of utilities that would be out of compliance.
However, detailed scenarios for the historical biogeography of Bauhinia and its relatives still need more robust dataset from palaeobotany and molecular phylogeny in future research.
In the case of certain hydrological data layers, such a consolidation of encoding may also require a harmonization process between both the VMap0 and its antecedent baseline the DCW in order to create a more robust seamless dataset.
In this paper, we report a significant dissimilarity, relating to the patient age distribution of infection, between the two circulating influenza A subtypes and provide a more robust statistical measure by combining several datasets and comparing the age distributions of the influenza A subtypes.
The next empirical strategy uses category variables and interaction terms to vastly expand the number of observations in the dataset and provide a more robust analysis of select variables.
