000			01538nam a22002177a 4500
999			_c4119 _d4119
005			20221013131753.0
008			221013b ||||| |||| 00| 0 eng d
020			_a9781544375229
082			_a519.536 _bFOX
100			_aFox, John _99316
245			_aRegression diagnostics: _ban introduction
250			_a2nd
260			_bSage Publications, Inc. _aCalifornia _c2020
300			_axv, 151 p.
365			_aUSD _b30.00
490			_aQuantitative Applications in the Social Sciences
520			_aRegression diagnostics are methods for determining whether a regression model that has been fit to data adequately represents the structure of the data. For example, if the model assumes a linear (straight-line) relationship between the response and an explanatory variable, is the assumption of linearity warranted? Regression diagnostics not only reveal deficiencies in a regression model that has been fit to data but in many instances may suggest how the model can be improved. The Second Edition of this bestselling volume by John Fox considers two important classes of regression models: the normal linear regression model (LM), in which the response variable is quantitative and assumed to have a normal distribution conditional on the values of the explanatory variables; and generalized linear models (GLMs) in which the conditional distribution of the response variable is a member of an exponential family
650			_aRegression analysis _92357
650			_aSocial sciences--Statistical methods _91897
942			_2ddc _cBK