This python project is a helper package that uses power analysis to calculate required sample size for any experiment
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Updated
Jan 3, 2025 - Python
This python project is a helper package that uses power analysis to calculate required sample size for any experiment
Free WordPress Plugin: Calculate the exact sample size and margin of error for your next survey or study. Use our free Sample Size Calculator for statistically accurate results. www.calculator.io/sample-size-calculator/
Monte Carlo power analysis tool for confirmatory factor analysis (CFA) sample size planning. Implements Wolf et al. (2013) with parallel simulation and targeted bias checks
Capstone projects of the Google Data Analytics Professional Certification
Learning materials, assignments, and helpful resources for professional certification. Completed October 2022
Official implementation of "Sample Size Determination: Posterior Distributions Proximity"
Undergraduate statistical research on minimax error spending and generalized Bonferroni allocation for multiple testing. Conducted with Dr. Michael Baron and presented at the Robyn Rafferty Mathias Student Research Conference.
Shiny app to compute the sample size for optimal designs for multivariate norming based on the methods developed in Innocenti et al. (2024, Journal of Educational and Behavioral Statistics, 49(5), 817-847)
This project is a Pinball designed experiment to determine the effect of different types of ball on the distance in which the ball is thrown. After gathering the data from thrown balls, a hypothesis test was done on the sample mean of each treatment (thrown ball) in a completely randomized design with an alpha around 0.05.
R scripts of Innocenti et al. (2021, Statistical Methods in Medical Research, 30(2), 357-375)
Shiny app to compute the sample size for optimal designs for univariate norming based on the methods derived in Innocenti et al. (2023, Psychological Methods, 28(1), 89–106)
Analyze Data with Python | Hypothesis Testing with Scipy | Sample Size Determination
This repository contains files for the project "Bayesian SSD with Attrition"
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