Statistics Education

  • 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.

    View Resource
    0
    No votes yet

  •  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.

    View Resource
    0
    No votes yet

  • 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.

    View Resource
    0
    No votes yet

  • 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.

    View Resource
    0
    No votes yet

  • This presentation is a part of a series of lessons on the Analysis of Categorical Data.  This lecture provides a review of probability and statistical concepts such as conditional probabilities, Bayes Theorem, sensitivity and specificity, and binomial and poisson distributions.

    View Resource
    0
    No votes yet

  • This is a graduate level introduction to statistics including topics such as probabilty/sampling distributions, confidence intervals, hypothesis testing, ANOVA, and regression.  Perfect for students and teachers wanting to learn/acquire materials for this topic.

    View Resource
    5
    Average: 5 (1 vote)

  • This course covers methodology, major software tools and applications in data mining. By introducing principal ideas in statistical learning, the course will help students to understand conceptual underpinnings of methods in data mining. It focuses more on usage of existing software packages (mainly in R) than developing the algorithms by the students. The topics include statistical learning; resampling methods; linear regression; variable selection; regression shrinkage; dimension reduction; non-linear methods; logistic regression, discriminant analysis; nearest-neighbors; decision trees; bagging; boosting; support vector machines; principal components analysis; clustering. Perfect for students and teachers wanting to learn/acquire materials for this topic.

    View Resource
    0
    No votes yet

  • The emphasis in this course will be understanding statistical testing and estimation in the context of "omics" data so that you can appropriately design and analyze a high-throughput study. Since the measurement technologies are evolving rapidly, important objectives of the course are for students to gain a basic understanding of statistical principles and familiarity with flexible software tools so that you can continue to assess and use new statistical methodology as it is developed for new types of data.

    By the end of the course, you should be able to tailor the analysis of your data to your needs while maintaining statistical validity.  You should come out of the course with insight so that you can assess the validity of new statistical methodologies as they are introduced as well as understand appropriate statistical analyses for data types not discussed in the class. 

    Perfect for students and teachers wanting to learn/acquire materials for this topic.

    View Resource
    0
    No votes yet

  • The objective of this course is to learn and apply statistical methods for the analysis of data that have been observed over time.  Our challenge in this course is to account for the correlation between measurements that are close in time. Perfect for students and teachers wanting to learn/acquire materials for this topic.

    View Resource
    0
    No votes yet

  • This is a graduate level survey course that stresses the concepts of statistical design and analysis in biomedical research, with special emphasis on clinical trials. Perfect for students and teachers wanting to learn/acquire materials for this topic.

    View Resource
    0
    No votes yet

Pages