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- W2071337532 abstract "This chapter deals with the very simple situation where the mean of a variable, the response variable, usually denoted Y, is linearly depending on another variable, the regressor, here denoted x1. The least squared method is used to get the parameter estimators and estimates of their precisions. This leads to design confidence and prediction intervals, significance tests, anova table. Residuals, diagnostics to identify influent observations and outliers are presented. Methods to detect departures from the model's assumptions and ways of dealing with these departures are addressed." @default.
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- W2071337532 date "2014-01-01" @default.
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- W2071337532 title "Simple Linear Regression" @default.
- W2071337532 doi "https://doi.org/10.1051/eas/1466003" @default.
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