19
votes
Accepted
If X=Y+Z, Is it ever useful to regress X on Y?
If you know $X = Y + Z$ and you have $Y$ and $Z$ measured, why would you need to run a regression of $X$ on $Y$ and $Z$? It provides no additional information and does not allow you to make "...
6
votes
If X=Y+Z, Is it ever useful to regress X on Y?
Linear regression is a tool that is used to achieve a goal. So any answer will depend on the goal to be achieved. As said already in the answer of @Noah, if you already know $X$, $Y$, and $Z$, I can't ...
5
votes
If X=Y+Z, Is it ever useful to regress X on Y?
Two people step on a scale. The scale outputs only the total weight of the couple.
If you know the weight of the first person ($Y$) can you guess what the scale will output ($X$) without knowing ...
2
votes
Accepted
How does a small range of the dependent variable affects linear regression?
Since your DV is naturally bounded between 0 and 100, but you have only observed values larger than 96, the lower bound is probably not going to be a problem. (Otherwise I would have looked at a beta ...
1
vote
Accepted
Linear regression decimal residuals below and above don't match exactly
Rounding is the culprit. Do it all with fractions to get the exact zero.
$$
x_1=12.2=\dfrac{366}{30}\\
x_2=15.5=\dfrac{465}{30}\\
x_3=16.6=\dfrac{498}{30}\\
\bar x = \dfrac{443}{30}\\
x_1-\bar x = \...
1
vote
Linear regression with Poisson distributed error term?
The model itself is quite weird and here are some example:
The response variable is count but the regression model is Linear. So you would expect to see some "Impossible" prediction like 7....
Only top scored, non community-wiki answers of a minimum length are eligible
Related Tags
linear × 1298regression × 871
r × 129
multiple-regression × 129
linear-model × 81
mixed-model × 76
least-squares × 69
machine-learning × 67
logistic × 61
model × 49
correlation × 45
regression-coefficients × 44
mathematical-statistics × 34
hypothesis-testing × 33
data-transformation × 32
residuals × 30
time-series × 29
variance × 29
self-study × 28
anova × 28
interaction × 28
generalized-linear-model × 26
p-value × 25
python × 23
classification × 22