On Mar 31, 2012, at 4:52 AM, Kamakshaiah wrote:
Dear Friends,
I had performed anova test on certain data frame (Health Care
Management) and got results [summary(aov)]. I am new to R and also
some extent to Statistics. Can somebody help me how should I interpret
these figures. I feel difficulty in interpreting values and respective
rows and columns.
The following is the result to which I request interpretation:
anova.stress$effects
Rather than trying to pull apart a summary.aov object when you admit
that you don't really know what you are doing, you should instead
first look at the output of functions (including the implicit `print`
function that will run when you simply type the object's name at the
console.)
(Intercept) heavy.drinking perceived.health
life.satisfaction
-127.7707327310 66.6366413568 58.0918782595
-6.9519755523 -0.7947641734
6.6881854290 13.3244486754 12.0570313711
14.1251305762 6.9407880977
7.7357329414 12.0627416985 -11.0900101005
1.2013513103 0.5663285592
For example if I am to talk about the very first value
-127.7707327310; what is this value is all about? and how it is
significant with respect to column headings. What is the last column?
anova.stress$qr
$qr
(Intercept) heavy.drinking perceived.health
life.satisfaction
1 -3.8729833462 -122.69732336064 -208.29402114263 -523.79543588447
2 0.2581988897 103.70798417437 82.62779609135 202.14890930300
3 0.2581988897 0.20254726362 71.69122174008 185.07374705668
4 0.2581988897 -0.65720148871 0.21700481702 7.77881765537
5 0.2581988897 -0.35155751874 0.49658862352 0.16955330300
6 0.2581988897 -0.01705521136 0.07303486380 0.13797897217
7 0.2581988897 -0.11154070424 -0.09755282025 0.28674472780
8 0.2581988897 -0.01186602555 0.26925236164 -0.12042327743
9 0.2581988897 0.18891427276 -0.01418690772 0.42333040781
10 0.2581988897 -0.34383207690 -0.59291615659 -0.25206212540
11 0.2581988897 -0.18887930130 0.11689140713 -0.58071444279
12 0.2581988897 0.13363607942 -0.35718909148 0.34481294660
13 0.2581988897 0.19904444749 -0.30629424692 -0.18166608573
14 0.2581988897 0.21462454012 0.09912429448 0.02910278133
15 0.2581988897 0.27300895524 -0.05280046529 -0.19460726218
I some how got idea (after studying) about QR, but here how should I
interpret these values?
Trying to teach yourself statistics this way is a bit like smashing a
watch with a hammer and then trying to understand how it works by
looking at each fragment.
$qraux
[1] 1.258198890 1.151445509 1.139760525 1.291373419
What are these values and how should I interpret them?
I confess that I have never asked myself that question. Attempting to
answer the question proved surprisingly difficult. The most complete
(?) description of that vector I could find is that it is "further
information required to recover the orthogonal part of the
decomposition". There is an answer in SO that uses the information,
but as to an "interpretation" I am unable to construct one:
http://stackoverflow.com/questions/3031215/mystified-by-qr-q-what-is-an-orthonormal-matrix-in-compact-form
anova.stress$rank
[1] 4
what does it mean rank 4?
Matrices have ranks. It has a variety of meanings. It specifies the
number of independent "dimensions" that the matrix will map onto. It
is the number of eigenvectors.
How can I know R and R square?
summary.lm(anova.stress) will have both an 'r.squared' element and
an adj.r.squared element. Generally the authors of R and the packages
will provided extraction functions for the summary measures they
consider useful.
Apart from the above 1) how can I interpret fitted and residuals? Can
I put the plot and show these values referring respective points in
the graph?
Get yourself a good introductory book or use one of the many
contributed documents on CRAN.
I request somebody to help interpret the above things?
Regards
M. Kamakshaiah
Assistant Professor, SCDL, Pune, India
--
David Winsemius, MD
West Hartford, CT
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