A quick "hands on" activity for an in-class experience of data collection as a simple linear regression example where students predict the time needed for a human chain of hand squeezes to make a full circuit as a function of number of people in the chain. The lesson plan secondary school lesson plan adapted from Cynthia Lanius’ hand squeeze activity by Bo Brawner at Tarleton State University.
This presentation was given by Aneta Siemiginowska at the 4th International X-ray Astronomy School (2005), held at the Harvard-Smithsonian Center for Astrophysics in Cambridge, MA.
This presentation was given by Aneta Siemiginowska at the 4th International X-ray Astronomy School (2005), held at the Harvard-Smithsonian Center for Astrophysics in Cambridge, MA.
This article gives a brief overview of the role of a biostatistician at NASA. It also provides names of those one can contact in this area.
Our online calculators and converters can help you in many daily tasks that require calculations to complete.
Free statistical calculators online. Our basic statistical calculators will help you in common tasks you might encounter and deal mostly with simple distributions.
Statistics is often taught as though the design of the data collection and the data cleaning have already been done in advance. However, as most practicing statisticians quickly learn, typically problems that arise at the analysis stage, could have been avoided if the experimenter had consulted a statistician before the experiment was done and the data were conducted. This course is created to provide an understanding of how experiments should be designed so that when the data are collected, these shortcomings are avoided. Perfect for students and teachers wanting to learn/acquire materials for this topic.
This chapter explains the structure/steps of hypothesis testing, the concept of significance, the relationship between confidence intervals and hypothesis testing, and Type I/II errors.
This text explains the differences between t-tests, z-tests, tests with proportions, and tests of correlation.
Analysis of variance (ANOVA) is used to test hypotheses about differences between two or more means. The t-test based on the standard error of the difference between two means can only be used to test differences between two means. When there are more than two means, it is possible to compare each mean with each other mean using t-tests. However, conducting multiple t-tests can lead to severe inflation of the Type I error rate. (Click here to see why) Analysis of variance can be used to test differences among several means for significance without increasing the Type I error rate. This chapter covers designs with between-subject variables.