Chapter 3. Statistical Data Analysis and Probability
We will cover the following recipes in this chapter:
- Fitting data to the exponential distribution
- Fitting aggregated data to the gamma distribution
- Fitting aggregated counts to the Poisson distribution
- Determining bias
- Estimating kernel density
- Determining confidence intervals for mean, variance, and standard deviation
- Sampling with probability weights
- Exploring extreme values
- Correlating variables with the Pearson's correlation
- Correlating variables with the Spearman rank correlation
- Correlating a binary and a continuous variable with the point-biserial correlation
- Evaluating relationships between variables with ANOVA
Introduction
Various statistical distributions have been invented, which are the equivalent of the wheel for data analysts. Just as whatever I think of comes out differently in print, data in our world doesn't follow strict mathematical laws. Nevertheless, after visualizing our data, we can see that the data follows...
