Resource Library

This program focuses on the teamwork required to produce a successful mission and the importance of statistics in project design and management. Using the video and a hands-on lesson, students learn about statistical analysis and how people use statistics, such as mean, median, mode and range, to make decisions. Members of the Penske Racing Team and engineers from Pratt & Whitney Rocketdyne help students investigate the relationship between work, energy and power as they look at race car design, the space shuttle and the International Space Station.

In this free online video program, "students will discover how to convert the standard normal and use the standard deviation; how to use a table of areas to compute relative frequencies; how to find any percentile; and how a computer creates a normal quartile plot to determine whether a distribution is normal. Vehicle emissions standards and medical studies of cholesterol provide real-life examples."

The Student Dust Counter is an instrument aboard the NASA New Horizons mission to Pluto, launched in 2006. As it travels to Pluto and beyond, SDC will provide information on the dust that strikes the spacecraft during its 14-year journey across the solar system. These observations will advance our understanding of the origin and evolution of our own solar system, as well as help scientists study planet formation in dust disks around other stars.

In this lesson, students explore the SDC data interface to establish any trends in the dust distribution in the solar system. Students record the number of dust particles, "hits," recorded by the instrument and the average mass of the particles in a given region.

The Student Dust Counter is an instrument aboard the NASA New Horizons mission to Pluto, launched in 2006. As it travels to Pluto and beyond, SDC will provide information on the dust that strikes the spacecraft during its 14-year journey across the solar system. These observations will advance human understanding of the origin and evolution of our own solar system, as well as help scientists study planet formation in dust disks around other stars. 

In this lesson, students learn the concepts of averages, standard deviation from the mean, and error analysis. Students explore the concept of standard deviation from the mean before using the Student Dust Counter data to determine the issues associated with taking data, including error and noise. Questions are deliberately open-ended to encourage exploration.

 The Integrated Medical Model (IMM) is a Monte Carlo simulation-based tool designed to quantify the probability of the medical risks and potential consequences that astronauts could experience during a mission. In this activity, students will use Monte Carlo methods with a TI-Nspire™ to simulate and predict probabilities of CO2 headaches aboard the ISS. 

NASA's Math and Science @ Work project provides challenging supplemental problems for students in advanced science, technology, engineering and mathematics, or STEM classes including Physics, Calculus, Biology, Chemistry and Statistics, along with problems for advanced courses in U.S. History and Human Geography.

The Neutral Buoyancy Laboratory allows astronauts an atmosphere resembling zero gravity (weightlessness) in order to train for missions involving spacewalks. In this activity, students will evaluate pressures experienced by astronauts and scuba divers who assist them while training in the NBL.  This lesson addresses correlation, regression, residuals, inerpreting graphs, and making predictions.

NASA's Math and Science @ Work project provides challenging supplemental problems for students in advanced science, technology, engineering and mathematics, or STEM classes including Physics, Calculus, Biology, Chemistry and Statistics, along with problems for advanced courses in U.S. History and Human Geography.

Math and Science @ Work presents an activity for high school AP Statistics students. In this activity, students will look at data from an uncalibrated radar and a calibrated radar and determine how statistically significant the error is between the two different data sets.

NASA's Math and Science @ Work project provides challenging supplemental problems for students in advanced science, technology, engineering and mathematics, or STEM classes including Physics, Calculus, Biology, Chemistry and Statistics, along with problems for advanced courses in U.S. History and Human Geography.

A song parody about how teachers lament that their students do not learn to think. Yet the exams they give only test memorization of rote facts. May be sung to the tune of Pete Seeger's "Where Have All the Flowers Gone." Lyrics written by Dennis Pearl with lots of help from Lawrence Mark Lesser (University of Texas, El Paso). Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.

November 14, 2006 webinar presented by Chrstine Franklin, University of Georgia, and Jessica Utts, University of California and hosted by Jackie Miller, The Ohio State University. In 2005 the American Statistical Association endorsed the recommendations of a report written by leading statistics educators, called "Guidelines for Assessment and Instruction in Statistics Education" (GAISE). The report had two parts - one for K-12 and one for the college introductory statistics course. In this webinar, two members of the report-writing team review the recommendations in the report, and provide suggestions for how to begin to implement them.

October 10, 2006 webinar presented By John Holcomb, Cleveland State University, and hosted by Jackie Miller, The Ohio State University. This webinar presents a quick overview of assessment methods related to student writing assignments and data analysis projects. Beginning with short writing assignments, Dr. Holcomb progresses through a range of different approaches to projects at the introductory course level. On-line resources containing existing project ideas will be shown along with ideas for creating one's own projects. The webinar also discusses several approaches to evaluating the range of assignments.