One never has an experience if By Prof Dr Sohail Ansari & A deeper meaning behind the contrast of night and day& Correlation, causation
Repeat experience as you did not know what to want
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One is condemned to
repeat experience if judgment that comes from experience is not good. One would,
however, never have an experience if one has a good judgment already that enables
him to know what to want
- Good judgment comes from
experience, and experience comes from bad judgment. Ambrose Bierce
- “Experience is what you get
when you didn't get what you wanted. And experience is often the most
valuable thing you have to offer.” ― Randy Pausch, The Last Lecture
A deeper meaning
behind the contrast of night and day
Quran tells us to look at the contrast between the night and the
day:
25:62 "And it is He Who made the Night and the Day to follow each other: for such as have the will to celebrate His praises or to show their gratitude".
25:62 "And it is He Who made the Night and the Day to follow each other: for such as have the will to celebrate His praises or to show their gratitude".
There is a deeper meaning
behind the contrast of night and day that has to do with our spiritual life. I
will come back to the meaning later.
Surat
ad-Dhuha (The Glorious Morning light) is revealed in a difficult
period of Prophet Muhammad's (s.a.w.) life. Every man gets
discouraged in times of adversity but in this Sura we are given the message
of hope by looking at Allah's past mercies. There are three
events in the early years of the Prophet's (s.a.w.) life that metaphorically
applies to all mankind. Allah tells the Prophet (s.a.w.) to look at his
past and see the wonderful mercies that has been bestowed upon
Him. Firstly the Prophet (s.a.w.) gets reminded of the fact that he
was an orphan and Allah gave him shelter (93:6). Secondly, the Prophet (s.a.w.) was
given guidance at a time when false worship was dominating (93:7). Third, that the Holy Prophet (s.a.w.)
was poor in wealth in his early years but by marrying Khadija
he become independent of worldly needs in his later
life (93:8). Allah reminds the Prophet (s.a.w) that he was never
forgotten in the past and wont be forgotten in the
future either.
Now
lets go back to the contrast of night and day. The first three verses of Surat
ad-Dhuha says the following:
93:1 "By the Glorious Morning
Light",
93:2 "And by
the Night When it is still",-
93:3 "Thy Guardian-Lord Hath not
forsaken thee, Nor is He displeased".
The
similarity of the night is the difficulties that life has to offer.
The stillness of night makes one feel like alone and
forsaken. We might feel lonely and discouraged when we
don't see immediate results of our struggle.
On
the other hand, the morning light of the sun shines with its splendor
and makes the dark and still night pass away. The similitude
of daylight is that Allah's care is always around a man and at the end the
result will always be pleasing. The stillness of night was only a
preparation for the upcoming daylight. So the night was never a waste. For those
who show gratitude, Allah's mercy will always come like
the daylight comes after a dark, long and still night. The Prophet
(s.a.w.) was promised full victory and satisfaction not only in the life of
this earth but also in there hereafter. He (s.a.w) was told to not be
discouraged and just wait; just as one has to wait for the glorious
morning sun after a long and dark night.
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Correlation, causation, and association - What does it all mean???
Adi Jaffe, Ph.D., is the
executive director of Alternatives Behavioral Health and a lecturer at UCLA and
California State University Long Beach
Let's clear something up, correlation isn't
causation, but it's important!
Posted Mar 30, 2010
A comment posted by a reader on a recent post reprimanded me for suggesting that marijuana caused relationships to go bad.
In
this instance the reader was mistaken, as I had specifically used the word
"associated", but the comment made me think that maybe I should
explain the differences between correlation, causation, and
association. I'm a scientist studying addiction, and
in the field, it's very important to be clear about what each of the words you
use means.
Being clear about inferences in research
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Correlation – a mutual relationship or connection between two or more
things. "research showed a clear
correlation between recession and levels of property crime"
synonyms: a mutual
relationship or connection between two or more things.
"research
showed a clear correlation between recession and levels of property
crime"
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When researchers find a
correlation, which can also be
called an association, what
they are saying is that they found a
relationship between two, or more, variables. For instance, in
the case of the
marijuana post, the researchers found an association between using
marijuana as a teen, and having more troublesome relationships in mid, to late,
twenties.
Correlations
can be positive - so that as one variable (marijuana smoking) goes
up, so does the other (relationship trouble); or they can be negative, which would
mean that as one variable goes up (methamphetamine smoking)
another goes down (grade point average). The trouble is that,
unless they are properly controlled for, there could be other variables
affecting this relationship that the researchers don't know about. For
instance, education, gender, and
mental health issues
could be behind the marijuana-relationship association (these variables were
all controlled for by the researchers in that study).
Researchers
have at their disposal a number of sophisticated statistical tools to control
for these, ranging from the relatively simple (like multiple regression) to
the highly complex and involved (multi-level modeling) and
structural equation modeling). These methods allow
researchers to separate the effect of one variable from others,
thereby leaving them more confident in
making assertions about the true nature of
the relationships they found. Still, even under the best
analysis circumstances, correlation is not
the same as causation.
Causation - When
an article says that causation was found, this means that the researchers found
that changes in one variable they measured directly
caused changes in the other. An example would be
Research showing that jumping
of a cliff directly causes great physical damage.
In
order to do this, researchers would need to assign people to
jump off a cliff (versus lets say jumping off of a 12 inch ledge) and measure
the amount of physical damage caused. When they find that jumping off the cliff
causes more damage, they can assert causality. Good luck recruiting for that
study!
Most
of the research you read about indicates a correlation between variables, not
causation. You can find the key words by carefully reading. If the article says
something like "men were found to have," or "women were more
likely to," they're talking about associations, not causation.
Why the difference?
The
reason is that in order to actually be able to claim causation, the
researchers have to split the participants into different groups, and assign
them the behavior they want to study (like taking a new drug), while the
rest don't. This is in fact what happens in clinical trials of medication because
the FDA requires proof that the medication actually makespeople better (more
so than a placebo). It's
this random assignment
to conditions that makes experiments suitable for the discovery
of causality. Unlike in association studies, random assignment assures (if
everything is designed correctly) that its the behavior being studied, and not
some other random effect, that is causing the
outcome.
Obviously,
it is much more difficult to prove causation than it is to prove
an association.
Should we just ignore associations?
No! Not at
all!!! Not even close!!! Correlations
are crucial for research and still need to be looked at and studied,
especially in some areas of research like addiction.
The
reason is simple - We
can't randomly give people drugs like methamphetamine as children and study
their brain development to see how the stuff affects them, that would
be unethical. So what
we're left with is a the study of what meth use (and
use of other drugs) is associated with. It's
for this reason that researchers use special statistical methods to assess
associations, making certain that they are also considering other things that
may be interfering with their results.
In
the case of the marijuana article, the researchers ruled
out a number of other interfering variables known to affect
relationships, like aggression, gender, education, closeness with other family
members, etc. By doing so, they did their best to assure that the association
found between marijuana and relationship status was real. Obviously other
possibilities exist, but as more researchers assess this relationship in
different ways, we'll learn more about its true nature.
This
is how research works.
It's
also how we found out that smoking causes cancer. Through endlessly repeated
findings showing an association. That turned out pretty well, I think...
Not even
close
What does that mean? Of course, I
can guess that it means "never" or "not at all". Is my
guess right? Can I use another word or sentence instead of that? Lastly, is it
slang?
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Yes, it means 'that's nowhere near the truth'. It isn't slang,
but it's likely to be found only in informal contexts.
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