What is regression through the origin?

Where we assume beta1 = 0, so our model becomes:

How does our estimate formulas change for regression through the origin?

How does our coefficient of determination change in regression through the origin?

r^2 becomes junk, instead we use raw r^2, which isn't comparable

When we scale Yi by w1 to Y*i, and Xi by w2 to X*i, how does things change our estimate formulas and other things?

What is this model?

log-log or log-linear (not log-lin)

In a log-log model, what does beta-2 represent?

The percentage change in Y that is expected from a percentage change in X

What is this model?

log-lin (not log-linear)

What does beta2 represent in the log-lin model?

The percentage change in Y that is expected from an absolute change in X

What model is this?

lin-log

What does beta2 represent in the lin-log model?

The absolute change in Y expected from a percentage change in X

Show the reciprocal model?

In the reciprocal model, where does Yi converge to?

The horizontal line Y=Beta1

In the reciprical model, what determines the slope of the SPR?

Beta2^. Positive Beta2^ means downward sloping, Negative Beta2& means upward sloping

What model is this?

An intrinsically non-linear model, which we cannot work with and which must be solved by algorythms on computers. And also, it smells.