The phrase "a large number of data points" is correct and usable in written English.
It can be used when discussing statistical analysis, research findings, or any context where data collection is relevant.
Example: "The study was robust due to the large number of data points collected over several years."
Alternatives: "a significant amount of data" or "a high volume of data points".
However, these methods are mathematically complex and often computationally slow for cases where a large number of data points are to be evaluated.
We do recommend that you use a purely algorithmic system, based on a large number of data points, to narrow the field before calling on human judgment to pick from just a few finalists—say, three.
Assessments of gm by the curve-fitting method require a large number of data points to be reliable82,83, it was only possible to perform this estimation in young leaves37,61.
Clusters containing a small number of sequences: The MLE and MCE learning approaches need a large number of data points to give robust estimates of the model parameters.
The plots at 850 km contain a large number of data points because this is the orbit altitude of the DMSP satellites.
An important point is that the algorithm is very well suited for the processing of force curves having a large number of data points (typically, the experimental force curves include from 2500 to 3000 data points).
Three-dimensional laser scanning supplies detailed and complete geometrical information in short working times, as a result of the acquisition of a large number of data-points that accurately model the detected surfaces.
Thus, it would be tempting for researchers to sample data at excessively high frequencies to obtain a sufficiently large number of data points, as opposed to collecting data for a prolonged period of time.
This is particularly likely to happen if the correction is not constrained by a sufficiently large number of data points.
Such studies yield a very large number of data points, so that investigation of how genes specifically contribute to a disease phenotype is challenging [ 19].
The long term optimization of a district energy system is a computationally demanding task due to the large number of data points representing the energy demand profiles.
