Timeline for Why is the slope not back transformed in a regression equation for allometric relationships
Current License: CC BY-SA 3.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jan 18, 2017 at 15:00 | vote | accept | adkane | ||
| Jan 17, 2017 at 22:53 | comment | added | adkane | Thanks. I just found it confusing because you use typically use the slope to find the estimate of the intercept. | |
| Jan 17, 2017 at 22:46 | comment | added | Comp_Warrior | @Manassa Mauler, Yes, the slope you are finding is for the logged data, thats why you need the power for it to make sense for the original data. | |
| Jan 17, 2017 at 22:36 | comment | added | adkane | Ah okay, so when I take the $log_{10}$ of my Y and X data I don't incorporate the coefficient estimate (i.e. the $\beta_1$ value which is the slope or q value in your answer). Rather it's because the slope is a coefficient of logged data in the first place that it's interpreted differently to the intercept. | |
| Jan 17, 2017 at 22:27 | history | answered | Comp_Warrior | CC BY-SA 3.0 |