Inferential Statistics
Inferential statistics is a branch of statistics that uses sample data to make predictions, inferences, or generalizations about a larger population. It involves techniques such as hypothesis testing, confidence intervals, and regression analysis to draw conclusions beyond the immediate data. This approach is fundamental for data-driven decision-making in fields like science, business, and social research.
Developers should learn inferential statistics when working with data analysis, machine learning, or A/B testing to validate hypotheses and make reliable predictions from limited data. It is essential for roles involving data science, analytics, or research, as it helps quantify uncertainty and assess the significance of findings, such as in user behavior analysis or model performance evaluation.