Science and Mathematics Education Commons^™

Teaching Business Statistics: Some Useful Relationships, Phil Rice, Chris Brune

Articles

The purpose of this paper is to suggest an instructional approach in the introductory business statistics course that utilizes relationships between separately introduced topics. The paper will explore three “useful relationships” that can assist classroom instruction: (1) the relationship between the simple arithmetic mean, the weighted arithmetic mean, and the expected value of a discrete probability distribution; (2) the relationship between the use of the multiplication rule to calculate the joint probability associated with two events, use of tree diagrams, and the use of the binomial and hypergeometric distributions; and (3) the relationship between the geometric mean and the compound …

Playfair's Introduction Of Bar And Pie Charts To Represent Data, Diana White, River Bond, Joshua Eastes, Negar Janani

Statistics and Probability

No abstract provided.

Representing And Interpreting Data From Playfair, Diana White, River Bond, Joshua Eastes, Negar Janani

Statistics and Probability

No abstract provided.

Seeing And Understanding Data, Beverly Wood, Charlotte Bolch

Statistics and Probability

No abstract provided.

Quantifying Certainty: The P-Value, Dominic Klyve

Statistics and Probability

No abstract provided.

Formative Evaluation Of A Web-Based Multimedia Intervention To Support Learning Of Statistics, Natalya Koehler, Ana-Paula Correia, Nimet Alpay, Carolyn Levally

All Faculty and Staff Scholarship

No abstract provided.

Gaiseing Into The New Guidelines, Robert Carver, Megan Mocko, Jeffrey Witmer, Beverly Wood

Publications

The first GAISE College Report came out in 2005. Over the past ten years our discipline has changed in many ways, including but not limited to what type of data is easily available, the technology that we use, as well as how we teach students. In this presentation we will briefly start with how the new GAISE 2016 guidelines and goals have changed, including the two new emphases of statistical thinking: giving students experience with multivariable thinking and with the investigative process. So how do you start to implement these new ideas? In this presentation, we will demonstrate an activity …

Gaise In Discipline-Specific Courses, Beverly Wood

Publications

While acknowledging the diverse setting, audience, and purpose of introductory courses, existing research assumes that courses offered by different disciplines share the same goals and teaching practices. The purpose of this study is to examine the objectives for student outcomes and pedagogical delivery of introductory statistics courses designed for students in a specific major, providing explicit evidence for this assumption.

The American Statistical Association’s Guidelines for Assessment and Instruction in Statistics Education (GAISE) are meant to apply to all introductory courses. The College Report’s Goals for Students and Recommendations for Teaching are used as a framework for a qualitative study …

A Bayesian Secondary Analysis In An Asthma Study, Samuel P. Wilcock, Vernon M. Chinchilli, Stephen P. Peters

ACMS Conference Proceedings 2011

A recent study published in the New England Journal of Medicine by the Asthma Clinical Research Network (ACRN) compared three different treatments for their effectiveness in treating adults with uncontrolled asthma. This paper will describe the study design and its results, then detail the beginnings of a secondary analysis using Bayesian methods to estimate the parameters of interest. The methods will be explained, and the preliminary estimates given and contextualized. The paper will conclude with a discussion of the next steps and the goals for further analysis of the data in this study.