A reciprocal transformation was used to linearise the $y$y-values from a bivariate set of data.
The equation of the least square line fitted to this data is $\frac{1}{y}=3-\frac{4x}{3}$1y=3−4x3.
Predict the value of $y$y when $x=2$x=2.
A $\log_{10}$log10 transformation was used to linearise the $y$y-values from a bivariate set of data.
The equation of the least square line fitted to this data is $\log_{10}y=2.9+1.2x$log10y=2.9+1.2x.
A reciprocal transformation was used to linearise the $y$y-values from a bivariate set of data.
The equation of the least square line fitted to this data is $\frac{1}{y}=-1.9-2.02x$1y=−1.9−2.02x.
A square transformation was used to linearise the $x$x-values from a bivariate set of data.
The equation of the least square line fitted to this data is $y=290+1246x^2$y=290+1246x2.