Module: Two sample methods

Module outline

This module discusses two-sample inference but first discusses the basic frame work for inference through the introduction to things that one should consider when comparing aspects of:

• Two distinct populations (e.g, delivery times of Uber Eat vs. Doordash)
• Two different treatments applied to one population (e.g., the effect of taking a drug vs. a placebo).

This involves the process of sampling data from a population or obtaining data via a randomize experiment to determine what can be inferred about the true effect or population based on sample results. Statistical inference helps us answer two questions about the population or experiment:

• How strong is the evidence of an effect?
• How large is the effect?

The first question is addressed using hypothesis testing, while the second question is address by a confidence interval.

While this framework is illustrated through two-sample method, this framework extends to any inferential procedures discussed in this resource.

• Module chapters:
  • Hypothesis testing and confidence interval framework
  • Inference for comparing two independent means