bivariate statistical measures
of regression correlation
bivariate statistical
measures
regression and correlation.
Dispersion diagram
simple linear regression
correlation
multiple regression
regression analysis model
Statistical: Allows the
incorporation of a random
component in the relationship.
standardized: the slope B 1 tells
us if there is a relationship
between two variables
deterministic: that under ideal
conditions, the independent
variable can be a mathematical
function of independent variables
problems with regression
inhomogeneous variance
nonlinear relationship
correlated errors
regression analysis
studies the relationship between two
quantitative variables
statistical technique used to derive an
equation that relates a criterion variable to
one or more predictor variables
studies the strength of the association through a
measure of association called the correlation
coefficient
simple regression
model
And the ŷ, since they rarely coincide, no matter how
good the regression model is, to the quantity "-e Y-ŷ" is
called the residual error.
We find a very simple-linear function of X, which allows
approximation by means of -ŷ=b0+ b1X
linear regression
pearson linear correlation coefficient
if the points have a tendency to line
up
r is useful to determine if there is a
linear relationship between two
variables. But it won't work for
(quadratic, logarithmic.
has the same sxy sign
covarianza de dos variables aleatorias X e Y
Entre dos variables, Sxy, nos indica si la relación entre dos variables es
directa o inversa
The sign of the covariance tells us that the cloud of points is increasing or
not, it says nothing about the degree of the relationship between
variables.