The most daunting question that students are mostly facing is "What is the best sample size?” A Statistical Power Analysis helps you identify the answer to this question. Performing power analysis and sample size estimation is an important aspect of experimental design, because without these calculations, sample size may be too high or too low. If sample size is too low, the experiment will lack the precision to provide reliable answers to the questions it is investigating. If sample size is too large, time and resources will be wasted, often for minimal gain.
Power analysis can be used to calculate the minimum sample size required so that one can be reasonably likely to detect an effect of a given size. Our analysts have experience in identifying the ideal sample size for research addressing the requirements of random sampling, multiple regressions, analysis of covariance, log-linear analysis, comparative analysis of subgroups, and other similar factors.