Further statistical reasoning
Check assumptions and bias and explain limits of testing and regression results.
Meaning
Hypothesis testing assesses how unusual data would be under an assumed model. Regression models relationships between variables. Conclusions depend on sample selection, model assumptions, and uncertainty.
Example
Under the assumption of a fair coin, one can calculate how plausible an extreme result such as 80 heads in 100 tosses would be and assess the assumption. This does not establish a cause from one result. A p-value is not the probability that a hypothesis is true. Statistical significance is also different from an effect being large or practically important.
Practice for this concept
Scope and references
Topics
Hypothesis testing, regression, data bias, limits of interpretation
Learning goal
Check assumptions and bias and explain limits of testing and regression results.
Helpful background
Review sampling and estimation assumptions and relationships between variables.
Further statistical judgment
These choice exercises calculate or judge specified finite data, trials, or assumptions. They do not establish data collection, written inference, model validation, or mastery of the whole statistics area.