research-expert

To calculate sample size for a two-sample t-test, you need to specify the expected effect size and desired statistical power. This research methodology skill provides Python scripts that compute the required sample size based on these parameters to ensure your experimental design is adequately powered.

For ANOVA and regression analysis, this skill utilizes Python libraries like numpy, scipy, pandas, and statsmodels. It provides functions to run descriptive statistics, t-tests, ANOVA, and regression, along with multiple testing corrections to validate your data analysis results.

Yes, you can generate block and stratified randomization using Python. This skill includes scripts for simple, block, and stratified randomization techniques, allowing you to properly assign subjects and minimize bias in your scientific experimental design.

Yes, this research methodology tool provides academic writing support. It offers guidance on structuring your manuscript, conducting literature reviews, and formatting citations correctly to adhere to academic writing standards.

You need multiple testing correction in statistical analysis when running multiple simultaneous tests to control the false-positive rate. This skill includes functions to apply corrections alongside t-tests, ANOVA, and regression to maintain the rigor of your research.