Episodes – Flash Statistics

01 – From Population to Sample [Link]
02 – The Statistical Disciplines [Link]
03 – Boxplot [Link]
04 – Organization of Data [Link]
05 – Boxplot 2° Episode [Link]
06 – Linear Regression (Intro) [Link]
07 – Sample Variance [Link]
08 – Principal Component Analysis (PCA) [Link]
09 – Clustering (Intro) [Link]
10 – Hypothesis Testing (General Overview) [Link]
11 – Law of Large Numbers [Link]
12 – Correlation vs Causality [Link]
13 – Statistical Wishes [Link]
14 – Histograms (Intro) [Link]
15 – Statistical Distributions [Link]
16 – P-Value [Link]
17 – Classification Problem [Link]
18 – Probability Mass Function [Link]
19 – Sample Mode [Link]
20 – Pie Chart [Link]
21 – Simpson’s Paradox [Link]
22 – Histograms 2° Episode (Class Width) [Link]
23 – Anscombe’s Quartet [Link]
24 – Association Rules (Intro) [Link]
25 – Poisson Distribution [Link]
26 – No Free Lunch Theorem [Link]
27 – Exponential Distribution [Link]
28 – Missing Values [Link]
29 – Decision Tree (Intro) [Link]
30 – Classification Problem (Performance Measure) [Link]
31 – Missing Values (Why Not Available?) [Link]
32 – Binomial Distribution [Link]
33 – Clustering Approaches (Hierarchical Methods) [Link]
34 – Central Limit Theorem [Link]
35 – Probability [Link]
36 – Weibull Distribution [Link]
37 – Random Variable (Definition and Types) [Link]
38 – Linear Regression (Best Fitting Line) [Link]
39 – Markov Chains (Intro) [Link]
40 – Training, Validation, Test [Link]
41 – Random Forest [Link]
42 – Markov Chains (Transition Probabilities) [Link]
43 – Frequentist vs Bayesian [Link]
44 – Scatter Plot [Link]
45 – Uniform Distribution [Link]
46 – Logistic Regression (Intro) [Link]
47 – Clustering Approaches (Partitioning Methods) [Link]
48 – Data Standardization [Link]
49 – Probability Interpretations [Link]
50 – Gaussian Distribution [Link]
51 – Quantiles [Link]