Titlebook: Regression Analysis with Applications; G. Barrie Wetherill,P. Duncombe,B. J. Vowden Book 1986 G. Barrie Wetherill 1986 ANOVA.analysis of v

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慢慢啃

Data exploration,ation of the data. For some sets of data this may just show a complete lack of unusual or interesting aspects. For others interesting observations, or groups of observations, unexpected structure or relationships may be found in the data. Failure to explore the data before embarking on a formal stat

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Multicollinearity,.-linear dependencies among the vectors of explanatory variables, so that if the Gaussian elimination of Section 3.2 were used to solve the least squares equations then at least one pivot would be near-zero. The effect of multicollinearity is to inflate the variance of the least squares estimator an

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integral

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記憶法

legacy

Predictions from regression,g the new values of the explanatory variables into the fitted regression equation, and this chapter concentrates mainly on interval estimates. Before going into the question of the variance associated with a prediction, we need to show clearly what the effect is of underfitting and overfitting. Both

誓言

Choosing a regression model,ecific case. For access to the literature see Hocking (1976,1983), Mosteller and Tukey (1977), Seber (1977), Thompson, (1978), Daniel and Wood (1980), and Miller (1984). This chapter presents a review of the main points and for further details these references should be consulted.