Jayasankar, J (2023) Non-parametric regression. In: Training Manual on Advanced Analytical Tools for Social Science Research Vol.2. CMFRI Training Manual Series No. 29/2023 . ICAR- Central Marine Fisheries Research Institute, Kochi, pp. 3-17.
|
Text
Winter School on Social Science Research_2023_Non-parametric regression_J Jayasankar.pdf Restricted to Registered users only Download (708kB) |
Abstract
It is common knowledge that to “regress” statistically is more a positive thing than is understood in literal parlance. The bonding as defined by regression manifests into many forms of relationships ranging from linear to more complicated non-linear, but all strongly founded on what is termed as distinct cause – effect relationship. The moment effects and cause(es) troop in myriads of possibilities flow out with a lot of statistical effervescence. The fizz at times touches fuzzy logic to interval data with rough set prospects too dangling in between. Thus any quantitative or quasiqualitative study on regression is replete with assumptions, options, manifestations and inferences
Actions (login required)
![]() |
View Item |
