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Searched for: Statistical Topic is Data Presentation -- Multivariate Quantitative Relationships
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View Resource Multiple Regression

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.

http://www2.chass.ncsu.edu/garson/pa765/regress.htm
View Resource IDEAL Modules

The modules in this collection discuss numerous statistical topics with examples and Java applets. Topics covered: Variable Types; Calculations; Histograms; Moments; Quantiles; Probability Definitions, Laws, and Simulations; Binomial, Poisson, and Normal Distributions, Normal Approximation to the Binomial, Central Limit Theorem, Confidence Intervals, Hypothesis Testing, Control Charts,...

https://ideal.stat.wvu.edu:8443/ideal/
View Resource Statistics Tools

This collection of calculators allows users to perform a number of statistical applications. Each provides background on the procedure and an example. Users can compute Descriptive Statistics and perform t-tests, Chi-square tests, Kolmogorov-Smirnov tests, Fisher's Exact Test, contingency tables, ANOVA, and regression.

http://www.physics.csbsju.edu/stats/
View Resource Webinar: Hand-size versus Height: a Real-time activity

November 24, 2009 Activity webinar presented by Carl Lee, Central Michigan University, and hosted by Leigh Slauson, Capital University. This webinar introduces a real-time online hands-on activity database for teaching introductory statistics. One particular activity, "How well can hand size predict height?", is used to engage students with a real-time activity in order to learn bivariate...

http://www.causeweb.org/webinar/activity/2009-11/
View Resource What Does It Take to Heat a New Room? Estimating Utility Demand in a Home

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.

http://www.amstat.org/publications/jse/v6n1/datasets.carver....
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