Sample size greatly reduces any error to randomness in a given sample.
Each experiment requires a proper size of a sample. The better it is fitted to the experiment, the better is the result.
For example, if you are trying to find out the study habits of students at your school of 1000 kids, a sample size of 50 would be sufficient. However, if you are trying to find out the study habits of students across the US, a sample size of at least several hundred-thousand would be required, preferably several million.
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The sample size has no effect on the validity of an experiment: instead, it is the experimental procedure and integrity of the experimenters.The sample size can affect conclusions that may be drawn from an experiment. The larger the sample is, the more reliable these conclusions are.
Statistically the larger the sample size the more significant the results of the experiment are. Chance variation is ruled out.
less bias and error occur when sample size is larger
The larger the sample size, the smaller the margin of error.
Estimates based on the sample should become more accurate.