Python Data Analysis Cookbook

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 ...