Asking for help with specific homework questions is
deprecated, as you should have seen in reading the
Statalist FAQ, but this seems rather different.
An FAQ cited there is
http://www.catb.org/~esr/faqs/smart-questions.html#homework
which says:
"Don't post homework questions
Hackers are good at spotting homework questions;
most of us have done them ourselves. Those questions
are for you to work out, so that you will learn from
the experience. It is OK to ask for hints, but not
for entire solutions."
In your case, it seems that you are being expected to learn
to walk and to run at the same time!
More concretely, a basic regression on a binary predictor
is equivalent to a t-test. Compare these results:
. sysuse auto
(1978 Automobile Data)
. ttest mpg, by(foreign)
Two-sample t test with equal variances
------------------------------------------------------------------------------
Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval]
---------+--------------------------------------------------------------------
Domestic | 52 19.82692 .657777 4.743297 18.50638 21.14747
Foreign | 22 24.77273 1.40951 6.611187 21.84149 27.70396
---------+--------------------------------------------------------------------
combined | 74 21.2973 .6725511 5.785503 19.9569 22.63769
---------+--------------------------------------------------------------------
diff | -4.945804 1.362162 -7.661225 -2.230384
------------------------------------------------------------------------------
diff = mean(Domestic) - mean(Foreign) t = -3.6308
Ho: diff = 0 degrees of freedom = 72
Ha: diff < 0 Ha: diff != 0 Ha: diff > 0
Pr(T < t) = 0.0003 Pr(|T| > |t|) = 0.0005 Pr(T > t) = 0.9997
. regress mpg foreign
Source | SS df MS Number of obs = 74
-------------+------------------------------ F( 1, 72) = 13.18
Model | 378.153515 1 378.153515 Prob > F = 0.0005
Residual | 2065.30594 72 28.6848048 R-squared = 0.1548
-------------+------------------------------ Adj R-squared = 0.1430
Total | 2443.45946 73 33.4720474 Root MSE = 5.3558
------------------------------------------------------------------------------
mpg | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
foreign | 4.945804 1.362162 3.63 0.001 2.230384 7.661225
_cons | 19.82692 .7427186 26.70 0.000 18.34634 21.30751
------------------------------------------------------------------------------
Also,
. scatter mpg foreign || lfit mpg foreign
shows graphically what you just did and help you think about R^2.
My other advice is to think in terms of good textbooks
first, not on-line resources.
Nick
n.j.cox@durham.ac.uk
Doug Mounce
> Any recommendations for a good on-line description and explanation
> for applying the multiple partial F-test? Also, what's the general
> way to think about using regress when the Y variable is continuous,
> but the X is binary?
>
> We've been learning in class how to describe the regress of one
> continuous variable on another, and I understand how to do a log
> transform and look for curvature or heteroscedasticity. We do
> jackknife residuals and some other diagnostics, and I'm stumped on
> how to describe the regress when the independent variable is
> binary.
> I can talk about the regression coefficient, I guess, but the R^2
> doesn't account-for much variation in this data.
>
> Sorry if asking for help with homework is bad form, but I'm
> also have
> a lot of clinical data that's binary and I thought that regression
> was pretty limited there. I'm an adult student with a job
> and family
> so finding a study group has been tough; any consideration of this
> request will be greatly appreciated
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