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  • Care must be taken in planning experiments so that the differences to be examined for significance should be those which furnish an answer to the question which we are asking. is a quote from British statistician William Sealy Gosset (a.k.a. Student: 1876 - 1937). The quote appears in a 1931 letter to "Biometrika" in which he was addressing some criticism of his work by Karl Pearson.
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  • A sketch by Anastasia Mandel reinterpreting "Sunset, Eagle Cliff, New Hampshire" by Jasper Francis Cropsey (1867) with the statistical caption "Regression tree, still standing after the trials." This is part of a collection of sketches by Anastasia Mandel and their accompanying statistical captions written by Stan Lipovetsky and Igor Mandel that took first place in the cartoon & art category of the 2009 A-Mu-sing contest sponsored by CAUSE. The collection and their accompanying statistical captions discussed in the paper "How art helps to understand statistics" (Model Assisted Statistics and Applications, 2009) by Stan Lipovetsky and Igor Mandel in volume 4 pages 313-324. Free to use in classrooms and on course websites.
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  • A sketch by Anastasia Mandel reinterpreting "Fruit Displayed on a Stand" by Gustave Caillebotte (1882) with the statistical caption "Cluster analysis: apples to apples, nuts to nuts - a statistician's dream." This is part of a collection of sketches by Anastasia Mandel and their accompanying statistical captions written by Stan Lipovetsky and Igor Mandel that took first place in the cartoon & art category of the 2009 A-Mu-sing contest sponsored by CAUSE. The collection and their accompanying statistical captions discussed in the paper "How art helps to understand statistics" (Model Assisted Statistics and Applications, 2009) by Stan Lipovetsky and Igor Mandel in volume 4 pages 313-324. Free to use in classrooms and on course websites.
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  • This collection of tutorials covers many statistical applications such as Pearson's Correlation Coefficient, Simple Linear Regression, One and Two Sample t-tests, Paired t-test, One-way Analysis of Variance (ANOVA), Mann-Whitney Test, Kruskal-Wallis Test, Friedman's Test, Interpreting p-values, Comparing two groups, Parametric and Nonparametric analyses, and Multiple Comparisons. The tutorials refer to the WINKS statistical software program, but they are useful for those who do not have access to WINKS.
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  • This page discusses the proper procedures for multiple comparison tests and reasons behind them.
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  • This tutorial introduces the basic concepts of probability using various examples. Topics include interpreting probability, calibration experiments, interpreting odds, sample space, basic rules, equally likely outcomes, constructing probability tables, unions and complements, mean, and two-way probability tables. A link to activities is also given.
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  • This tutorial explains the theory and use of Multiple Regression and demonstrates it with an example on SAT scores and GPA. Data is given as well as SPSS and Minitab code.
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  • This resource explains Multiple Regression and concepts associated with it. Key Words: Predicted values; Residuals; Dummy Variables; Interaction Effects; T-Test; Regression Coefficients; Correlation; Partial Correlation; R-Squared; Adjusted R-Squared; Multicollinearity; Variance-Inflation Factors; Transformation; Cook's Distance; Validity; Durbin-Watson Coefficient.
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  • This article describes a dataset containing energy use data for single-family homes and monthly weather data in the Boston area over a seven year period. The data can help illustrate concepts like central tendency, dispersion, time series analysis, correlation, simple and multiple regression, and variable transformations. Key Words: measurement; forecasting.
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  • This article describes a dataset containing information on bacterium culturing. Students can use graphical methods, one-way and two-way ANOVA, and multiple polynomial regression to estimate the optimal conditions for bacteria growth. Key Words: Analysis of variance; Exploratory data analysis; Interactions; Optimisation; Outlier.
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