RoboSathi

Chi-Square Goodness of Fit Test | Chi- Square Test | Hypothesis Testing | Explained with Example

Vector | Transpose of a Vector | Vector Fundamentals | Explained

Chi- Square (χ²) Test Statistic for Categorical Data | Hypothesis Testing

Chi-Square Distribution | Hypothesis Testing

Z test of Proportion | Gaussian Distribution | Hypothesis Testing | A/B Testing | Example

Z Test | Gaussian Distribution | Standard Error | Hypothesis Testing | Explained with Example

Z-Score | Gaussian Distribution | Hypothesis Testing | Explained with Example

2-Sample T Test for Equal & Unequal Variance | Welch's T Test | Hypothesis Testing | Explained

1 Sample T Test | Hypothesis Testing | Explained with Example

Student’s T Test | T Distribution | Degrees of Freedom | Hypothesis Testing | Explained with Example

Probability for Machine Learning

Understanding Effect Size | Cohen’s d - How big is the effect | Hypothesis Testing | Explained

Power of a Test in Hypothesis Testing | Explained with Example

Left Tailed | Right Tailed | Two Tailed or Sided HypothesisTest | Explained with Example

Framework for Hypothesis Testing | Null & Alternate Hypothesis | P Value | Explained with Example

Hypothesis Testing | Null Hypothesis | Alternate Hypothesis | Types of Hypothesis Test | Explained

Confidence Interval | Meaning of Confidence Level | Explained with Example

Central Limit Theorem | Standard Error | Explained with Intuition, Formula & Example

Correlation vs Causation Explained | Why Correlation Does NOT Mean Causation

Correlation | Pearson Correlation Coefficient | Spearman's Rank Correlation Coefficient | Explained

Covariance Explained | Direction of Relationship Between Two Variables | Explained with Example

Measures of Position | Percentile | Quartile | Inter Quartile Range | Explained with Example.

Measures of Dispersion | Range, Variance, Standard Deviation, Skewness & Kurtosis | Simplified

Measure of Central Tendency | Mean, Median & Mode | Explained with Example

Minimum Mean Square Error (MMSE) Estimation for Machine Learning | Explained with Example

Maximum A- Posteriori (MAP) Estimation for Machine Learning | Explained with Example

Bayesian Statistics for Machine Learning | Prior , Likelihood & Posterior | Explained with Example

Maximum Likelihood Estimation (MLE) for Machine Learning | Intuition + Worked Example

Parametric Model Estimation for Machine Learning | Explained with Example

Jensen–Shannon (JS) Divergence for Machine Learning | Relation with KL Divergence | Explained