## Design Tools

### Statistical Power

Statistical power tools include tutorials and applications to perform a number of power analyses in order to compute test power and size of test estimates. You can read about power here.

| | Name: Link(s) | Description | Application | More Information: |

| | **GLM Power for Categorical Factors**
| Approximates power for categorical generalized linear model effects. | Design
| Approximates power for effects in a generalized linear model for experiments with categorical factors. Currently supports Logit, Poisson, and linear regression. |

| | **Categorical Analysis Power**
| Calculates power for test configurations with categorical factors. | Design
| The Categorical DOE application allows the user to calculate power for a variety of test configurations and can support decisions related to sample size selection. |

| | **One Sample Proportion Test Power**
| Estimates and plots power by sample size for a one sample proportion test. | Design
| One sample proportion tests are useful for scenarios where sample proportions are being compared to a baseline or expected value. For instance, this test could be used to assess if the proportion of target hits from operational testing surpasses a requirement threshold (e.g. 70% target hit requirement). The one sample proportion test power application guides sample size selection. |

| | **One Sample ***t*-test Power
| Estimates and plots power by sample size for a one sample t-test. | Design
| One sample t-tests are useful for scenarios in which sample data that are continuous (distance, speed, etc.) are compared to a baseline or expected value and the population variance is unknown. For instance, this test could be used to assess if the average miss distance found during testing surpasses a requirement (e.g. requirement states average miss distance must be less than 10 yards). The one sample t test power application is a tool designed to guide sample size selection. |

| | **Two Sample Proportion Test Power**
| Estimates and plots power by sample size for a two sample proportion test. | Design
| Two sample proportion tests are useful for scenarios where evaluators are interested in comparing proportions from two samples. For instance, this test could be used to compare the proportion of target hits from a new system to the results from a test of a legacy system. The two sample proportion test power application is a tool designed to guide sample size selection. |

| | **Two Sample ***t*-test Power
| Estimates and plots power by sample size for a two sample t-test. | Design
| Two sample t-tests are useful for scenarios when evaluators want to compare two sample means for continuous data (distance, speed, etc.). For instance, this test could be used to assess if the average miss distance for a new system is smaller than the average miss distance for a legacy system. The two sample t test power application is a tool designed to guide sample size selection. |

| | **Power in JMP Tutorial**
| Provides detailed instructions for calculating power for designed experiments in common software packages. | Design
| Provides an overview of power calculations and detailed instructions for calculating power for designed experiments across a variety of software packages. |

### Other Design Tools

| Name: Link(s) | Description | Application |