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Lines, regression and some relations between slopes and intercepts considered from a geometric viewpoint
Author(s) -
Runcie Dennis,
Neggers Joseph,
Hsia W. S.
Publication year - 1991
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/j.2044-8317.1991.tb00948.x
Subject(s) - transformation (genetics) , mathematics , regression , geometric pattern , geometric transformation , geometric mean , statistics , regression analysis , type (biology) , geometric shape , pure mathematics , computer science , geometry , artificial intelligence , image (mathematics) , geology , paleontology , biochemistry , chemistry , gene
Recently, Valentine, Wilding & Mohindra (1984) argued that the negative correlation between slopes and intercepts sometimes found in memory‐scanning tasks can be explained on purely statistical grounds. Because theory underlying the memory‐scanning literature is so emphatic in stating that this should not be so, a more exhaustive examination of other possibilities was undertaken. In this paper we consider a more geometric approach and observe that the geometric properties of the transformation x → x + t determine the correlations obtainable from the variables ‘slope’ and ‘intercept’ associated with the kinds of data given in memory scan experiments. The family of lines produced are naturally negatively correlated for good geometric reasons. Even though our observations do not contradict the conclusions obtained by Valentine et al ., our method is sufficiently different to be considered in its own right. It is hoped that the geometric considerations of the type presented here may find application in interpreting data obtained from families of regression lines representing runs of experiments.