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.
It will decrease too. * * * * * If it is the confidence interval it will NOT decrease, but will increase.
less bias and error occur when sample size is larger
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 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.
The confidence interval becomes smaller.
Statistically the larger the sample size the more significant the results of the experiment are. Chance variation is ruled out.
It will decrease too. * * * * * If it is the confidence interval it will NOT decrease, but will increase.
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.
The statistics of the population aren't supposed to depend on the sample size. If they do, that just means that at least one of the samples doesn't accurately represent the population. Maybe both.
less bias and error occur when sample size is larger
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.
Better the results
In a scientific experiment, the control group and the experimental group are treated the same way except for the variable being tested. Because the margins of error increase as the sample size gets smaller, both groups should be the same size.
yes the size is 4444