Statistics and machine learning
59 videos • 4,546 views • by yuzaR Data Science
1
Introduction to statistics: The (small) Big Picture or how to solve 95% of statistical problems
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2
Linear regression vs. Statistical tests ⚔ who wins?
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3
Logistic regression: or what is the probability of success?
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4
From Confusion Matrix to ROC curve: or the link between machine learning and epidemiology
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5
Survival analysis 1: a gentle introduction into Kaplan-Meier Curves
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6
Survival analysis 2: Parametric Exponential Models
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7
Box-Plots with Statistical Details - all you need to know
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8
Box Plots in R with t-test, Mann-Whitney, ANOVA, Kruskal-Wallis, Shapiro-Wilk, Levene and post-hocs
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9
R demo | ANOVA & Kruskal-Wallis + post hocs & p-value-correction
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10
R demo | How to visualize models Part 1 | multiple linear models, all assumptions & post-hocs
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11
R demo | How to visualize models Part 2 | non linear, logistic, multinomial, mixed effects, survival
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12
R package reviews | performance | Check ALL model assumptions at once! Check model quality!
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13
R package reviews | janitor | clean your data!
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14
R package reviews | dlookr | diagnose, explore and repair your data quick!
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15
R demo | How to impute missing values with machine learning
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16
R demo | Automated Exploratory Data Analysis (EDA) Reports (with only 1 function for each report)
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17
R demo | Deep Exploratory Data Analysis (EDA) | explore your data and start to test hypotheses
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18
What is a P-value, why we need it and how to use it correctly (+ Type I Error & Type II Error)
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19
R demo | Chi-Square Test | How to conduct, visualize and interpret | + pairwise post-hoc tests
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20
R demo | One Sample T-Test & One Sample Wilcoxon Test | How to conduct, visualize and interpret
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21
R demo | Correlation | Pearson, Spearman, Robust, Bayesian | How to conduct, visualise and interpret
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22
R demo | Correlation Matrix | How to conduct, visualise and interpret
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23
R demo | Paired Wilcoxon Signed Rank Test | How to conduct, visualise and interpret
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24
R demo | Paired Samples t-Test | How to conduct, visualise and interpret
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25
R demo | Repeated Measures ANOVA (One-Way) | How to Conduct, Visualise and Interpret
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26
R demo | Friedman Test | How to Conduct, Visualise and Interpret
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27
R demo | McNemar Test | How to Conduct, Visualise and Interpret
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28
R demo | Cochran’s Q Test + Pairwise McNemar Tests (post-hoc)
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29
R demo | Two-Samples t-Test | Student’s & Welch’s | How to conduct, visualise, interpret & more 😉
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30
R demo | Mann-Whitney U Test = Wilcoxon Rank Sum Test | How to conduct, visualise, interpret & more😉
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31
R demo | ANOVA (One-Way) | Fisher’s, Welch’s, Bayesian, Robust | Conduct, visualise, interpret + 😉
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32
R demo | Kruskal-Wallis test + Post-Hoc | How to conduct, visualize, interpret & more 😉
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33
Tidy Data and Why We Need It!
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34
R package reviews | glmulti | Find The Best Model !
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35
R package reviews | report | Report Statistical Results of Tests, Models, Data!
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36
R package reviews | sjPlot | Easily Visualize Data And Model Results
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37
R demo | Robust Regression (don't depend on influential data)
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38
R demo | Many (Grouped / Nested) Models Simultaneously are Very Effective
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39
4 Reasons Non-Parametric Bootstrapped Regression (via tidymodels) is Better then Ordinary Regression
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40
Effective Resampling for Machine Learning in Tidymodels {rsample} R package reviews
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41
R package reviews {gtsummary} Publication-Ready Tables of Data, Statistical Tests and Models!
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42
Quantile Regression as The Most Useful Alternative for Ordinary Linear Regression
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43
{emmeans} Game-Changing R-package Squeezes Hidden Knowledge out of Models!
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44
Don’t Ignore Interactions - Unleash the Full Power of Models with {emmeans} R-package
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45
Top 10 Must-Know {dplyr} Commands for Data Wrangling in R!
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46
Mastering {dplyr}: 50+ Data Wrangling Techniques!
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47
Transform Your Data Like a Pro with {tidyr} and Say Goodbye to Messy Data!
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48
Combine Tables with {dplyr}
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49
Join Tables with {dplyr}
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50
Conditioning with {dplyr} Modify Your Data Quick
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51
Quantile Regression Reporting Made Easy: How to Create Stunning Plots and Tables in Minutes!
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52
Master Simple Linear Regression with Numeric Predictor in R
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53
Multivariable Linear Regression in R: Everything You Need to Know!
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54
Data Reveals | How to be Successful and Happy | How to avoid being Poor and Unhappy (4K)
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55
Exact Binomial Test Explained! + Real-World Example: Counting Trash in the Baltic Sea 📊🌊🔬(4K)
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56
Logistic Regression Basics Explained: Probabilities, Odds, Odds-Ratios and Log-Odds-Ratios (4K)
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57
Mastering Logistic Regression with Categorical Predictors: Always Positive Odds Ratios (4K)
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58
Not Linear Relationship Between Numeric Predictor and Binary Outcome in Logistic Regression (4K)
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59
Multivariable Logistic Regression in R: The Ultimate Masterclass (4K)!
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