Mean
Average of Y values.
X Std. Dev Standard deviation for X: a measure of how dispersed the x data values are
about the mean.
Y Std. Dev Standard deviation for Y: a measure of how dispersed the y data values are
about the mean.
X Population Dev Population Standard deviation for X: a measure of how dispersed the X data
values are about the mean, assuming the data constitutes a complete set of
data.
Y Population Dev Population Standard deviation for Y: a measure of how dispersed the y data
values are about the mean, assuming the data constitutes a complete set of
data.
S.E.SamP.X Sample error for X: a measure of how dispersed the X data values are about
the mean sample standard deviation, assuming the data is a sampling of a
larger, more complete data set.
S.E.SamP.Y Sample error for Y: a measure of how dispersed the Y data values are about
the mean sample standard deviation, assuming the data is a sampling of a
larger, more complete data set.
Pred X Predicts X for a given hypothetical value of Y, based upon the model calculated
to fit the data.
Pred Y Predicts Y for a given hypothetical value of X, based upon the model calculated
to fit the data.
a The
a
coefficient for the chosen regression model, which is the slope for a linear
model.
b The
b
coefficient for the chosen regression model, which is the y-intercept for a
linear model.
Correlation The correlation coefficient for the given (x, y) data. The correlation coefficient is
a number in the range -1 through 1 that measures how closely the calculated
line fits the data.
Covariance A measure of how much two variables change in relation to one another.
Sigma X The sum of the x values.
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General
Weight and Dimensions
