This page has two calculators. One will cacluate a simple logistic regression, while the other calculates the predicted probability and odds ratio. There is also a brief tutorial covering logistic regression using an example involving infant gestational age and breast feeding. Please note, however, that the logistic regression accomplished by this page is based on a simple, plain-vanilla empirical regression.
This page will calculate the intercorrelations (r and r2) for up to five variables, designated as A, B, C, D, and E.
This page will calculate the intercorrelations (r) for any number of variables (V1, V2, V3, etc.) and for any number of observations per variable.
The page will calculate the following: Exact binomial probabilities, Approximation via the normal distribution, Approximation via the Poisson Distribution. This page will calculate and/or estimate binomial probabilities for situations of the general "k out of n" type, where k is the number of times a binomial outcome is observed or stipulated to occur, p is the probability that the outcome will occur on any particular occasion, q is the complementary probability (1-p) that the outcome will not occur on any particular occasion, and n is the number of occasions.
Given a sample of N values of X randomly drawn from a normally distributed population, this page will calculate the .95 and .99 confidence intervals (CI) for the estimated mean of the population.
In this free online video program, "students will understand inference for simple linear regression, emphasizing slope, and prediction. This unit presents the two most important kinds of inference: inference about the slope of the population line and prediction of the response for a given x. Although the formulas are more complicated, the ideas are similar to t procedures for the mean sigma of a population."
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.