Correlation

  • Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write! Quote from the presidential address in 1951 of mathematical statistician Samuel S. Wilks (1906 - 1964) to the American Statistical Association found in "JASA",Vol. 46, No. 253., pp. 1-18. Wilks was paraphrasing Herbert G. Wells (1866 - 1946) from his book "Mankind in the Making". The full H.G. Wells quote reads: "The great body of physical science, a great deal of the essential fact of financial science, and endless social and political problems are only accessible and only thinkable to those who have had a sound training in mathematical analysis, and the time may not be very remote when it will be understood that for complete initiation as an efficient citizen of one of the new great complex worldwide States that are now developing, it is as necessary to be able to compute, to think in averages and maxima and minima, as it is now to be able to read and write."
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  • A quick pun about "autocorrelation" by Bruce White.
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  • This article discusses teaching causality without being discipline specific. It explains the causal differences between description, prediction and explanation.
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  • This activity uses a computer program to explore probability concepts such as sample space, independent events, law of large numbers, and reliability. An outline of the activity and the computer program are provided.
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  • This article describes a dataset on life expectancies, densities of people per television set, and densities of people per physician in various countries of the world. The example addresses correlation versus causation and data transformations. Key Word: Prediction.
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  • This article describes a dataset containing information on economic class of passengers and mortality rates from the sinking of the Titanic. The dataset can be used to foster statistical thinking by giving students the data and asking them to determine the source.
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  • This lesson describes bootstrapping in the context of a statistics class for psychology students.
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  • This random number generator produces a data table with up to 10 columns and up to 2500 rows. For random integers, users must specify the data range. For data from a Normal (Gaussian) distribution, users specify mean and standard deviation.

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  • This Flash applet provides an introduction to simple linear regression for introductory statistics students. It combines a brief narrated animation with an interactive scatterplot function. Students are able to place points on the scatterplot by clicking with a mouse or typing X-Y coordinates. Students use these points to learn about the best fit line by placing a guess on the plot and comparing it with the least squares line. Students also learn about the value of the correlation coefficent and points that would be considered outliers. Students may also specify a value of x (within the range of the data) and obtain the resulting predicted value.
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  • This correlation and regression example compares performance on reading comprehension questions to performace on the SAT. It also compares those who read the passage referred to by the questions to those who did not. Exercise questions and answers are also provided.
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