Introduction to Statistical Investigations

Introduction to Statistical Investigations
by

Nathan Tintle, Beth Chance, George Cobb, Allan Rossman, Soma Roy, Todd Swanson, and Jill VanderStoep

Applets | Data Sets | Applets & Data for iPad and other Mobile Devices | Informational Videos | Text Website at Wiley

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Winner of MAA's 2018
Daniel Solow Author's Award

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Introduction to Statistical Investigations is an introductory statistics text developed at Hope College, Dordt College, Cal Poly, and Mount Holyoke and the first edition is available from John Wiley & Sons. (Text Website at Wiley)

The text differs from traditional texts in both content and pedagogy. Statistical inference is introduced using simulation-based methods in Chapter 1. This allows students to intuitively understand the process of inference from the very beginning of their course. Concepts of statistical inference are then explored for the entire text instead of only the last half of many traditional texts. Students are actively engaged in the material through numerous activities in which they flip coins, draw cards, collect data, do computer simulations and run experiments. Computer simulations are done with freely available applets. (See Efficacy Flyer for information on student performance.)

We are currently working on an assessment initiative of our curriculum, other randomization curriculums, and more traditional introductory statistics curriculums. This assessment will include pre- and post- concepts and attitudes assessments as well as common exam questions. We are looking for participants and non-users of our curriculum are especially needed. Our goals are to determine what works, what doesn’t, comparisons by institution, instructor, style, etc. If you participate you will receive Individualized instructor reports to learn about your own students outcomes.

For more information about our curriculum or participation in our assessment efforts described above contact Nathan Tintle at nathan.tintle@dordt.edu.

Workshops since 2014

Papers written by the authors about our curriculum

"Assessing the Association Between Precourse Metrics of Student Preparation and Student Performance in Introductory Statistics: Results from Early Data on Simulation-Based Inference vs. Nonsimulation-Based Inference", Journal of Statistics Education (2018), Winner of 2019 JSE best paper award
“Student Gains in Conceptual Understanding in Introductory Statistics with and without a Curriculum Focused on Simulation-Based Inference,” Proceedings from the 10th International Conference on Teaching Statistics. (2018)
“Assessing Retention of Statistical Concepts after Completing a Post-Secondary Introductory Statistics Course,” Proceedings from the 10th International Conference on Teaching Statistics. (2018)
“Can a Simulation-Based Inference Course be Flipped?” Proceedings from the 10th International Conference on Teaching Statistics. (2018)
“Finding Meaning in a Multivariable World: A Conceptual Approach to an Algebra-Based Second Course in Statistics,” Proceedings from the 10th International Conference on Teaching Statistics. (2018)
“Assessing Simulation-Based Inference in Secondary Schools,” Proceedings from the 10th International Conference on Teaching Statistics. (2018)
“Assessing the Association between Quantitative Maturity and Student Performance in an Introductory Statistics Class: Simulation vs. Non-Simulation-Based,” Proceedings from the 10th International Conference on Teaching Statistics. (2018)
“Development of a Tool to Assess Students’ Conceptual Understanding in Introductory Statistics,” Proceedings from the 10th International Conference on Teaching Statistics. (2018)
"Student Performance in Curricula Centered on Simulation-Based Inference: A Preliminary Report," Journal of Statistics Education (2017)
"Broadening the Impact and Evaluating the Effectiveness of Simulation-based Curricula for Introductory Statistics," Proceedings of the TUES/AAAS PI’s conference. Washington, DC. (2016)
"Combating anti-statistical thinking through the use of simulation-based methods throughout the undergraduate curriculum," The American Statistician (2015)
"Challenging the state of the art in postintroductory statistics: preparation, concepts and pedagogy," Proceedings of the World Congress on Statistics (2014)
"Using simulation/randomization to introduce p-value in week 1," Proceedings from the 9th International Conference on Teaching Statistics (2014)
"Quantitative evidence for the use of simulation and randomization in the introductory statistics course," Proceedings from the 9th International Conference on Teaching Statistics (2014)
"Impact of a simulation/randomization-based curriculum on student understanding of p-values and confidence intervals," Proceedings from the 9th International Conference on Teaching Statistics (2014)
"Student attitudes toward statistics from a randomization-based curriculum," Proceedings from the 9th International Conference on Teaching Statistics (2014)
"Using simulation-based inference for learning introductory statistics," WIREs Computational Statistics (2014)
"Retention of statistical concepts in a preliminary randomization-based curriculum," Statistics Education Research Journal (2012)
"Development and assessment of a preliminary randomization-based introductory statistics curriculum," Journal of Statistics Education (2011) (Winner of Best JSE Paper Award)

This material is based upon work supported from the National Science Foundation under (Grant DUE-1140629) and (Grant DUE-1323210 )

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.