Python is a general-purpose, high-level language that makes statistical and data-oriented work practical through readable code and mature libraries. section 1.0 section 1.8
Python supports workflows that turn data questions into inspectable results:
- Calculate descriptive statistics such as means, medians, modes, variances, standard deviations, interquartile ranges, and proportions. section 1.0
- Analyze samples and populations, then use confidence intervals and hypothesis tests to quantify uncertainty. section 1.0
- Fit linear and logistic regression models to investigate relationships or make predictions. section 1.0 section 1.8
- Handle numerical work, tabular data, and visualizations with NumPy, pandas, and Matplotlib. section 1.8
From workplace polling to an evidence-based claim
A workplace poll can use Python to summarize responses, compare a sample with the wider employee population, and assess whether the results are reliable rather than treating a percentage as automatic truth. section 1.0 section 1.8
