now here on the component matrix this
tells us some information about how each
of the individual items do in terms of
getting at that component so what we
have here is notice we have our five
items SW LS one through five and then we
have this column four component and we
have these different values here and in
a one component solution it's pretty
nice as this works out very cleanly and
what I mean by that is that these are
called component loadings or people
might call them factor loadings and they
tell you how strong the relationship is
between the item and the component in
our solution and if you look at these
values here they can be interpreted in a
principal components analysis with a one
component solution these are literally
just the Pearson correlation of the item
with the component or we can think of as
factor so SW s1 correlates or loads
people will say 0.74 seven on the
component s wls two loads are correlates
in this case point eight on the
component and so on and if we look here
our highest loading item is s2 BLS three
which loads or correlates if we round
here 0.89 on that component which is
very high so whatever st plus 3 is
measuring and as a reminder that
question said I am satisfied with my
life this loads or correlates the
highest on the component of any of the
items now that being said it should be
noted here that all of these items
correlate or load very highly on the
component it's just that st plus 3 loads
the highest but s2 BLS two and four load
very high as well and so does st plus
five and one for that matter as well
five is has the lowest loading but 0.7
one is still quite good in practice
and in fact there are some rules that
people use here in terms of trying to
interpret whether or not an item loads
in a meaningful way on a component and
in this case like I said all of these do
but people will use I've seen a variety
of rules varying from if these are 0.3
or higher all the way to 0.5 or higher
as being important or noteworthy so in
other words if s to be oz 1 was let's
say 0.2 for for example then using the
rule of 0.3 I would say this item does
not load meaningfully on the component
if it was 0.25 but it's not it's 0.75 so
it loads quite high on the component and
all of these do but there are a variety
of rules 0.3 0.4 0.5 sometimes people
will calculate what the significance
should be at alpha 0.05 for these
loadings and interpret them that way and
so on but here ours are all very high
this is a very clean solution it's a
pretty straightforward solution which I
wanted to use here for your first look
of principal component analysis as I
think it's best to use a simple solution
and then build from there to more
complex ones
