Final answer:
The researcher needs to ascertain the expected effect size when determining the needed sample size for a study with an alpha of .01 and a power of .80. Effect size, along with variability in the population and the research hypothesis, are crucial for an accurate sample size calculation and for reducing the chances of Type I and Type II errors.
Step-by-step explanation:
In determining the needed sample size for a study with an alpha of .01 and a power of .80, the researcher must ascertain the expected:
The correct answer to this question is effect size.
The power of a statistical test is the probability that the test correctly rejects a false null hypothesis (i.e., it correctly detects an effect when there is one), which is 1 minus the probability of making a Type II error (β). To calculate the required sample size for a given study, several factors need to be considered, including the acceptable Type I error rate (α), which is given as .01 in this case, and the desired power of the test (1 - β), which is stated as .80.
However, the effect size is a critical component which represents the magnitude of the difference one is attempting to detect between groups or treatments, and this must be specified to determine the appropriate sample size. Additionally, understanding the variability in the population, which can affect the total variance associated with the measures used, is also essential for an accurate sample size determination. Finally, formulating the research hypothesis specifies the expected relationship or difference that the study is designed to detect, which in turn influences the calculation of effect size.