Causality

Statistical Thinking for Data Science Data science blends math with real problems. Statistical thinking helps turn data into knowledge. It asks for evidence, not belief. It reminds us to quantify uncertainty and to compare options using data. Start with a clear question. Decide who the data are about (the population) and how you will collect it (the sample). Plan to minimize bias in sampling. When results depend on the data, explain how sure we are. A simple plan helps you stay honest. ...

Data Science and Statistics for Decision Making Data science and statistics help turn raw numbers into decisions. They start with a clear goal, collect relevant data, and use simple models to forecast outcomes. The aim is to quantify uncertainty and present it in plain language so teams can act with confidence. A few basic ideas travel across many fields: data quality matters, not every data point helps, and the real value lies in understanding how likely different results are. Distinguish signal from noise, and use probability to describe possibilities rather than promises. ...