You'll find out:
✅ Variance and standard deviation
✅ Normal distribution and distribution with a long tail
✅ Three-sigma rule
✅ Normalizing distributions with a long tail: log, boxcox, sqrt
✅ Quantitative (continuous and discrete) and categorical (qualitative and ordinal) variables
✅ Sum and cumulative sum
✅ Visualization: box plot, histogram, bar plot.
✅ Standard error
✅ Analysis of normal distribution (qq-plot)
✅ Population, sample, and representative sample
✅ Sampling bias (selection bias)
✅ Coefficient of variation
✅ Range (interval of variation) and quantile range
✅ Measures of central tendency and dispersion
✅ Skewness of the distribution: right-skewed and left-skewed
✅ Long-tailed distribution
✅ Normalizing the distribution using: log, boxcox, and sqrt
✅ Histogram, boxplot
✅ Mean, median, percentile
✅ Types of variables (categorical and numerical)
✅ Numerical feature parameters: central tendency (mean, median), variation parameter, positional parameters, asymmetry parameter
✅ Categorical (and sometimes numerical) feature indicators