Increasing the sample size results in an increased frequency of detecting marker/phenotype associations [ 40].
Because the margin of sampling error is related to the size of the sample, increasing the sample size for a particular subgroup through the use of oversampling allows for estimates to be made with a smaller margin of error.
Approximately results are consistent by increasing the sample size.
Error in sampling can be reduced by increasing the sample size.
Weaknesses in data can be effectively addressed by increasing the sample size.
It is simply seen that the value of error decreases by increasing the sample size.
However, increasing the sample size could improve the performance of the OLS-based model.
Stratified sampling allows increasing the sample size in a region by a few to many additional sample units.
However, as it is depicted in Fig. 4, the computational time increases by increasing the sample size.
Members of our lab have studied many quantitative aspects of movies, incrementally increasing the sample size as we have progressed.
The result suggests that predictions using RFBC can always achieve the same level of accuracy by increasing the sample size.
