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Students' Understanding Of The Concepts Involved In One-Sample Hypothesis Testing, Harrison Stalvey, Annie Burns-Childers, Darryl Chamberlain, Aubrey Kemp, Leslie Meadows, Draga Vidakovic
Students' Understanding Of The Concepts Involved In One-Sample Hypothesis Testing, Harrison Stalvey, Annie Burns-Childers, Darryl Chamberlain, Aubrey Kemp, Leslie Meadows, Draga Vidakovic
Publications
Hypothesis testing is a prevalent method of inference used to test a claim about a population parameter based on sample data, and it is a central concept in many introductory statistics courses. At the same time, the use of hypothesis testing to interpret experimental data has raised concerns due to common misunderstandings by both scientists and students. With statistics education reform on the rise, as well as an increasing number of students enrolling in introductory statistics courses each year, there is a need for research to investigate students’ understanding of hypothesis testing. In this study we used APOS Theory to …
Real Data Is Messy... And Manageable, Beverly Wood, Carl Clark
Real Data Is Messy... And Manageable, Beverly Wood, Carl Clark
Publications
Using real data in an introductory statistics course is a delicate balance between reality and manageability. The internet is awash with data that is useful for students to answer questions of interest to them but it is not always formatted as neatly as textbook data. The ASA's recently endorsed GAISE College Report 2016 points to the plausibility of considering multivariable thinking even if only at a rudimentary level. With both messy and multivariable data in mind, we present some activities/projects and sources for data to give introductory students the opportunity to engage with real data.
Multivariate Thinking In An Intro Stats Course – Is It Possible?, Beverly Wood
Multivariate Thinking In An Intro Stats Course – Is It Possible?, Beverly Wood
Publications
Many of our students have an intuitive sense that there is more to the story than univariate or bivariate data can tell us. We can acknowledge and encourage that habit of digging deeper by demonstrating some ways to look at additional variables. Simpson’s paradox and side-by-side scatter plots are ways to provide a glimpse of more complex analysis that are accessible to students in an introductory course with or without strong quantitative skills.