Random error and sample size have an inverse relationship...As sample size INCREASES random error DECREASES.
There's a good explanation at the related link.
The larger the sample, the lower the % error.. so to reduce a % error, increase your sample size.
how to reduce the problem of random error and systematic error while doing an experiment
Increasing the sample size generally enhances the accuracy and reliability of statistical estimates. As the sample size grows, the standard error decreases, leading to narrower confidence intervals and greater precision in estimating population parameters. This also increases the likelihood of detecting a true effect if one exists, thereby improving the power of statistical tests. Overall, larger sample sizes reduce the impact of random variation and yield more consistent results.
Increase sample size.
... should be increased by a factor of 4. Note that this implies that the only errors are statistical (random) in nature; increasing the sample size won't improve systematic errors.
You can overcome or reduce the problem of random error and systematic error while doing an experiment by increasing the sample size, which means averaging over a huge number of observations.
It should reduce the sample error.
Personal error can be minimized by providing proper training and clear guidelines to the individuals involved. Random error can be minimized by increasing sample size, repeating experiments, and using precise measurement tools.
The larger the sample, the lower the % error.. so to reduce a % error, increase your sample size.
how to reduce the problem of random error and systematic error while doing an experiment
Increase sample size.
... should be increased by a factor of 4. Note that this implies that the only errors are statistical (random) in nature; increasing the sample size won't improve systematic errors.
A random sample is a selection from the population of interest where each item (persons, households, widgets, etc.) has an equal chance of being selected. The idea being that measuring a random sample of sufficient size will accurately (within a margin of error) reflect the "true" value that exists in the population - while at the same time reducing your study to a manageable size. A random sample is integral in good survey design to reduce bias in your experiment.
Increase n or sample size.
The basic requirement for a sample is that it should be representative of the population from which it is drawn, ensuring that the findings can be generalized. Additionally, the sample size should be adequate to provide reliable and valid results, minimizing sampling error. Random selection methods are often employed to enhance the sample's representativeness and reduce bias.
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The margin of error is reduced.