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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.

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How does sample size affect the experiment?

The sample size determines the accuracy of results in an experiment


How does sample size affect an experiment or the result of an experiment?

Sample size significantly impacts the reliability and validity of an experiment's results. A larger sample size generally increases the statistical power, reducing the margin of error and enhancing the ability to detect true effects or differences. Conversely, a smaller sample size may lead to unreliable or biased results, increasing the risk of Type I or Type II errors. Thus, adequate sample size is crucial for drawing meaningful and generalizable conclusions from experimental data.


How does sample size affect validity of results in a research?

A large sample reduces the variability of the estimate. The extent to which variability is reduced depends on the quality of the sample, what variable is being estimated and the underlying distribution for that variable.


How does the sample size affect an experiment?

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.


What is the benefit of using a large sample size in an experiment?

Statistically the larger the sample size the more significant the results of the experiment are. Chance variation is ruled out.


What combination of variables will make an experiment the most reliable?

To make an experiment more reliable, it is important to have a large sample size, control for confounding variables, and ensure replicability by conducting the experiment multiple times. These factors reduce the impact of chance and increase the validity of the study findings.


How do you determine an adequate sample size?

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.


How does size of target population affect sample size?

The size of the target population directly influences the required sample size for accurate representation and statistical validity. Larger populations generally require larger sample sizes to capture the diversity and variability within the population. However, after a certain point, increasing the population size has a diminishing effect on the required sample size, as the necessary sample size plateaus. This is due to the law of diminishing returns in sampling, where a sufficiently large sample can provide reliable estimates regardless of further population increases.


Why would having a larger sample size be a better idea than having a samll sample size when doing an experiment?

less bias and error occur when sample size is larger


What is least likely to affect the validity of a public opinion poll or survey?

The size of the survey sample is least likely to affect the validity of a public opinion poll or survey, as long as it is conducted randomly. Other factors, such as biased questioning, nonresponse rate, or sampling method, are more likely to impact validity.


What is wrong with this experiment?

It is difficult to determine without more specific details about the experiment. Common issues could include a lack of control group, insufficient sample size, bias in data collection, or flawed methodology. It is important to identify and address any potential flaws to ensure the experiment's validity and reliability.


How does sample size affect the margin of error?

The larger the sample size, the smaller the margin of error.