Statistical Thinking
As our society increasingly calls for evidence-based decision making, it is important to consider how and when we can draw valid inferences from data. This module will use four recent research studies to highlight key elements of a statistical investigation.
Learning Objectives
- Define basic elements of a statistical investigation.
- Describe the role of p-values and confidence intervals in statistical inference.
- Describe the role of random sampling in generalizing conclusions from a sample to a population.
- Describe the role of random assignment in drawing cause-and-effect conclusions.
- Critique statistical studies.
Chapter Authors: Beth Chance & Allan Rossman
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Beth Chance
Beth Chance is Professor of Statistics at Cal Poly – San Luis Obispo. She is a Fellow of the American Statistical Association, the inaugural winner of the Waller Education Award for excellence and innovation in teaching undergraduate statistics, and a 2011 MERLOT Classics Award for technology tools development.
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Allan Rossman
Allan Rossman, Professor of Statistics at Cal Poly – San Luis Obispo, has written curricular materials and conducted many faculty development workshops related to undergraduate statistics education. He is a Fellow of the American Statistical Association and a recipient of the Mathematical Association of America’s Haimo Award for Distinguished Teaching.
