What impact would using a much smaller sample have on the accuracy of your results
A sample size that is too small increases the likelihood of a Type II error skewing the results, which decreases the power of the study.
The standard error is dependent on sample size: larger sample sizes produce smaller standard errors, which estimate population parameters with higher precision. Scientists need to test more samples in their experiments to increase the certainty of their estimates.
Higher sample size allows the researcher to increase the significance level of the findings, since the confidence of the result are likely to increase with a higher sample size. This is to be expected because larger the sample size, the more accurately it is expected to mirror the behavior of the whole group.
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