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.
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.
The sample size determines the accuracy of results in an experiment
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.
A sample size is needed whenever you conduct an experiment. How you determine an adequate sample size depends on the scope of what you're testing, such as medications.
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.
Better the results
Margin of error, level of significance and level of power are all elements that will affect the determination of sample size.
It should reduce the sample error.
1. Better chance of uniform sample. 2. Material for confirmations if needed.
having a large sample size