Foundations of statistics for data scientists with R and Python
- Boca Raton : Chapman and Hall/CRC, 2022
- xvii, 467 p. ; ill. , 26 cm
9780367748456
Python AIC (Akaike information criterion) Bayesian inference Bonferroni method Chi-squared distribution Conditional association Delta method Estimation Explanatory variables Generalized linear models Histogram Inteval estimate Likehood ratio test M-estimation Monte Carlo methods Normal distribution Overdistribution Overdispersion P-value Poisson distribution Quasi-complete separation Random variable Sampling test Significance test Skewed distributions T statistic Wilcoxon test