Power Analysis &
Sample Size Calculation Help
Students & Researchers
What is a Power Analysis?
The purpose of a power analysis is to provide you with information needed to address your research question(s) in an accurate fashion. Power analysis is an important aspect of any quantitative study. Before going further it is important to define power. Power is broadly defined as the probability that a statistical significance test will reject the null hypothesis or the ability of a statistical test to detect an effect, given that the effect actually exists. Request Power Analysis Help Today
Numerically, power is equal to 1-b (beta). In order to reject the null hypothesis (which states that there is no relationship between the variables of interest), power should be at least .80. In general, the larger your sample size, the greater the power. Sometimes having too many subjects can decrease your power. Increasing sample size can also significantly increase your costs. A power analysis can help you decide in advance the amount of subjects needed to make your study worthwhile. We can help you conduct your power analysis to ensure you choose the appropriate statistical test(s) and effectively plan your data collection.
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Let Us Help Conduct Your Power Analysis
Given the importance of a power analysis, it is important that it is conducted properly and explained in simple language. In addition, if you are unsure about how to increase power, the effect size required for your study or differences between power value means, let us conduct your power analysis and explain the various components to you. If you are unsure what statistical test might be the most appropriate and powerful for your study, let us review your research question to help you choose the best statistical test
for your study. Request Power Analysis Help Today
Power Analysis Examples
Given the complexities of power analysis, we have created a few articles that provide examples of power analysis as it relates to different statistical analyses. Check out power analysis and sample size calculations for:
» Pearson Correlations
We realize these examples may not address all your power analysis questions and are ready to assist you with your specific dissertation needs.
» Multiple Regression
» Logistic Regression
» Chi Square
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