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Searched for: Application Area is Biology
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View Resource Using EDA, ANOVA and Regression to Optimise some Microbiology Data

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.

http://www.amstat.org/publications/jse/v12n2/datasets.binnie...
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....
View Resource Sexual Activity and the Lifespan of Male Fruitflies: A Dataset That Gets Attention

This article presents a dataset from an experiment designed to test if increased reproduction reduces longevity for male fruitflies. The data are in .dat format. Key Words: Analysis of variance; Contrasts; Experimental design; Regression; Precision; Statistical interaction; Survival analysis.

http://www.amstat.org/publications/jse/v2n1/datasets.hanley....
View Resource Exploring Relationships in Body Dimensions

This article presents a dataset containing physical measurements for 507 physically active individuals. These data can be used to demonstrate simple descriptive statistics, least squares and multiple regression, or discriminant and classification analysis. The data are in .dat format.

http://www.amstat.org/publications/jse/v11n2/datasets.heinz....
View Resource Quantitative Environmental Learning Project

This site provides numerous datasets for graphical display topics including linear, exponential, logistic, power rule, periodic, and other bivariate scatterplots, histograms, and other univariate data. Each data set is accompanied with a description, file format options, and a sample graph.

http://www.seattlecentral.edu/qelp/Data.html
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