Small collection of numerical experiments
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Updated
Mar 22, 2018 - R
Small collection of numerical experiments
Statistical analysis on the Italian firms
An R project that investigates and visualizes the effect of sex and education on an individual's income level through the use of a full-factorial two-way ANOVA test and relevant post hoc significance tests conducted over a 2014 Pew Research Center dataset consisting of higher education attainment, gender, and income data.
R Shinyapp to calculate sample size for a given power
Exercises for Hypothesis tests including ANOVA, Chi-Square, T-test, Non Parametric tests
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.
Running various statistical tests with R and R-studio to analyze manufacturing specifications and ensure lot integrity
Aplikasi Shiny untuk membandingkan ketegaran dan kuasa uji t (klasik) dan uji Welch terhadap dua sampel.
A Recalibrated Hypothesis Test for SNP-Level Summary Statistics
Applied Statistical Learning, A/B testing with Marketing Analytics, Data Analytics for Business Intelligence
Statistics Projects for Intro to Statistics, and Probability & Statistics courses at Ashoka
In this case study, we have provided the average life expectancy of people of 193 Countries. We have to predict next year's value using linear regression.
In this project, I wrote R codes to conduct hypothesis test of two population proportions on the terminated food recalls dataset to see if the year 2021 has less cases of terminated food recalls than the previous year.
Statistical hypothesis testing regarding mutations in unc-43 gene of C. elegan species
R interface & extension to an adapted Persistence Landscapes Toolbox
Using R to for hypothesis testing, by comparing means and fitting distributions curves. From data generating to hypothesis testing.
This R script analyses COVID-19 data focusing on death rates, age, and gender effects on mortality. It computes descriptive statistics, cleans data, calculates death rates, performs hypothesis testing, and evaluates claims regarding age and gender effects on death.
R interface for estimated kernel densities comparisons
An R package for regression analysis of data from extreme sampling
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