Power Analysis Calculator

The Statistical Power Analysis Calculator helps users determine the statistical power, Type II error rate, required sample size for 80% power, and critical value for various hypothesis tests using inputs such as significance level, effect size, sample size, and test type.

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Step-by-Step Guide to Using the Statistical Power Analysis Calculator

Understanding the Input Fields

This calculator helps you perform a statistical power analysis by allowing you to input specific variables and then calculating different results based on these inputs. Before using the calculator, it is crucial to understand the input fields available.

Step 1: Enter the Significance Level (α)

Start by entering the Significance Level (α). This value represents the probability of making a Type I error, commonly set at 0.05. You can input any value between 0.001 and 0.1 with increments of 0.001. This field is required.

Step 2: Specify the Effect Size (d)

Input the Effect Size (d), an estimate of the strength of the phenomenon being measured. You should provide a value between 0.1 and 2, in steps of 0.01. This field is also required for the calculation.

Step 3: Determine the Sample Size (n)

Enter the Sample Size (n), which represents the number of observations or participants in your study. The valid input range is from 2 to 1000, with a step of 1. This field is a crucial part of the power analysis and must be filled in.

Step 4: Select the Test Type

Choose the Test Type from the given options: One-tailed or Two-tailed. This decision impacts the critical value calculation and the power analysis. Selecting one of these options is mandatory.

Understanding the Result Fields

After entering all the required inputs, the calculator will provide several result values to help you assess your study’s power and error rates.

Step 5: Review the Statistical Power (1-β)

The Statistical Power (1-β) will be displayed as a percentage with two decimal places. This value represents the probability of correctly rejecting a false null hypothesis. The calculator uses the formula: 1 - pow((1 - effectSize), (sampleSize - 1)) to determine this power.

Step 6: Check the Type II Error Rate (β)

The Type II Error Rate (β) is also shown in percentage form. It indicates the probability of falsely accepting a null hypothesis when it is not true, calculated simply as 1 - statisticalPower.

Step 7: Evaluate the Required Sample Size for 80% Power

For planning purposes, the Required Sample Size for 80% Power field displays the sample size needed to achieve an 80% statistical power. This calculation uses the formula: ceil(log(0.2) / log(1 - effectSize) + 1).

Step 8: Analyze the Critical Value

The calculator outputs a Critical Value to help you determine the point beyond which the null hypothesis would be rejected. It is calculated using 1.96 * (testType == 1 ? 1 : 2) and shown with three decimal places.

Final Remarks

By carefully following these steps and interpreting the results, you can perform a comprehensive power analysis to inform your statistical study planning and execution effectively.