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000150192 0500_ $$aHA31.3$$b.L48
000150192 0820_ $$a519.5/36$$219
000150192 1001_ $$aLewis-Beck, Michael S.
000150192 24510 $$aApplied regression :$$ban introduction /$$cMichael S. Lewis-Beck.
000150192 260__ $$aBeverly Hills, Calif. :$$bSage Publications,$$cc1980.
000150192 300__ $$a79 p. :$$bill. ;$$c22 cm.
000150192 4901_ $$aSage university papers series. Quantitative applications in the social sciences ;$$vno. 07-022
000150192 504__ $$aBibliography: p. 77
000150192 5050_ $$a1. Bivariate regression: fitting a straight line -- Exact versus inexact relationships -- The least squares principle -- The data -- The scatterplot -- The slope -- The intercept -- Prediction -- Assessing explanatory power: The R² -- R² versus r -- 2. Bivariate regression: Assumptions and inferences -- The regression assumptions -- Confidence intervals and significance tests -- The one-tailed test -- Significance testing: a rule of thumb -- Reasons why a parameter estimate may not be significant -- The prediction error for Y -- Analysis of residuals -- The effect of safety enforcement on coal mining fatalities: a bivariate regression example -- 3. Multiple regression -- The general equation -- Interpreting the parameter estimates -- Confidence intervals and significance tests -- The R² -- Predicting Y -- The possibility of interaction effects -- A four-variable model: overcoming specification error -- The multicollinearity problem -- High multicollinearity: an example -- The relative importance of the independent variables -- Extending the regression model: dummy variables -- Determinants of coal mining fatalities: a multiple regression example -- What next?
000150192 650_0 $$aRegression analysis.
000150192 830_0 $$aQuantitative applications in the social sciences ;$$vno. 07-022.
000150192 85200 $$bgen$$hHA31.3$$i.L48
000150192 909CO $$ooai:library.usi.edu:150192$$pGLOBAL_SET
000150192 980__ $$aBIB
000150192 980__ $$aBOOK