1) The probability that a test will correctly reject the null hypothesis: 

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Power (Power is the probability of making a correct decision (to reject the null hypothesis) when the null hypothesis is false.)

2. An estimate of the range of values likely to be included within a given proportion of a sampling distribution 

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Confidence Interval (A range or interval of values used to estimate the true value of a population parameter.)

3. Effect size describes the strength of the relationship, in relation to sample size and average variation

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If the effect size of the intervention is large, it is possible to detect such an effect in smaller sample numbers, whereas a smaller effect size would require larger sample sizes. In an analysis of variance, the effect size can be interpreted as the proportion of variance explained by a certain effect versus total variance.

4. The estimated variation in the population

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Standard deviation (A standard deviation is a sample estimate of the population parameter, that is, it is an estimate of the variability of the observations.)