yuzaR Data Science

R demo | Automated Exploratory Data Analysis (EDA) Reports (with only 1 function for each report)

Histograms and Density Plots with {ggplot2}

Top 10 Must-Know {dplyr} Commands for Data Wrangling in R!

R package reviews | DataExplorer | explore your data quick!

What is a P-value, why we need it and how to use it correctly (+ Type I Error & Type II Error)

R demo | How to impute missing values with machine learning

Master Simple Linear Regression with Numeric Predictor in R

{emmeans} Game-Changing R-package Squeezes Hidden Knowledge out of Models!

Bar Charts with {ggplot2}

Effective Resampling for Machine Learning in Tidymodels {rsample} R package reviews

Quantile Regression Reporting Made Easy: How to Create Stunning Plots and Tables in Minutes!

Master Box-Violin Plots in {ggplot2} and Discover 10 Reasons Why They Are Useful

Conditioning with {dplyr} Modify Your Data Quick

Logistic Regression Basics Explained: Probabilities, Odds, Odds-Ratios and Log-Odds-Ratios (4K)

R demo | Automated Exploratory Data Analysis (EDA) Reports (with only 1 function for each report)

9 FLAWS of ‘Summary’ Function You DIDN’T Know About and How to Fix Them

Multivariable Linear Regression in R: Everything You Need to Know!

Mastering Logistic Regression with Categorical Predictors: Always Positive Odds Ratios (4K)

Not Linear Relationship Between Numeric Predictor and Binary Outcome in Logistic Regression (4K)

Exact Binomial Test Explained! + Real-World Example: Counting Trash in the Baltic Sea 📊🌊🔬(4K)

Combine Tables with {dplyr}

Don’t Ignore Interactions - Unleash the Full Power of Models with {emmeans} R-package

Join Tables with {dplyr}

R demo | Kruskal-Wallis test + Post-Hoc | How to conduct, visualize, interpret & more 😉

7 Reasons to Master Scatter Plots in {ggplot2} with World Happiness Data

Data Reveals | How to be Successful and Happy | How to avoid being Poor and Unhappy (4K)

Survival analysis 1: a gentle introduction into Kaplan-Meier Curves

Correlation in R | Pearson, Spearman, Robust, Bayesian | How to conduct, visualise and interpret

From Confusion Matrix to ROC curve: or the link between machine learning and epidemiology

Transform Your Data Like a Pro with {tidyr} and Say Goodbye to Messy Data!

Quantile Regression as The Most Useful Alternative for Ordinary Linear Regression

PERFECT TABLES IN

Mastering {dplyr}: 50+ Data Wrangling Techniques!

FIND THE BEST MODEL

4 Reasons Non-Parametric Bootstrapped Regression (via tidymodels) is Better then Ordinary Regression

R demo | Two-Samples t-Test | Student’s & Welch’s | How to conduct, visualise, interpret & more 😉

Report Tests, Models, Data

R demo | Paired Samples t-Test | How to conduct, visualise and interpret

R demo | Robust Regression (don't depend on influential data)

R demo | McNemar Test | How to Conduct, Visualise and Interpret

R demo | Chi-Square Test | How to conduct, visualize and interpret | + pairwise post-hoc tests

R demo | One Sample T-Test & One Sample Wilcoxon Test | How to conduct, visualize and interpret

R demo | Many (Grouped / Nested) Models Simultaneously are Very Effective

R demo | Correlation Matrix | How to conduct, visualise and interpret

PERFECT PLOTS IN

Hypothesis Testing and why we need it

R demo | Mann-Whitney U Test = Wilcoxon Rank Sum Test | How to conduct, visualise, interpret & more😉

R demo | Friedman Test | How to Conduct, Visualise and Interpret

R demo | Paired Wilcoxon Signed Rank Test | How to conduct, visualise and interpret

DEEP Exploratory Data Analysis (EDA) | explore your data and start to test hypotheses

Tidy Data and Why We Need It!