Philosophies are existentially determined doctrines By Prof Dr Sohail ansari
After the major sins which must be avoided, the
greatest sin is that someone dies in a state of debt and leaves behind no asset
to pay it off. (Darimi)
Sociology
of illusion
All philosophies are ‘the systems of thought
conceived by the selective and the fallible mind as an ideal type’ and ‘thought
of as an ideal type’ is an inspirations followers borrow from their guru.
All social and political doctrines which
passed for knowledge are seen by the benefit of hindsight as existentially
determined doctrines; elaborate rationalizations of the interests of classes
which distorted the actualities of social life in serving those interests. The
Sociology of knowledge consequently has turned out to be no more than the
sociology of illusion creating the intellectual paralysis of total
skepticism.
1.
“The more important reason is that the research itself
provides an important long-run perspective on the issues that we face on a
day-to-day basis. ” -Ben
Bernanke
2.
“Research is
formalized curiosity. It is poking and prying with a purpose. ” -Zora Neale Hurston
3.
“To understand how
consumers really think and feel, it is vital to go beyond words.” -Katja Bressette
4.
“Research is about
engaging in a conversation with a brand.” -Matthew Rhodes
This
lesson explores the terminology of experimental design. What are variables? How
do they influence each other? Is it possible that you are seeing connections
that don't actually exist?
https://statistics.laerd.com/
Research
As a researcher, you're
going to perform an experiment. I'm kind of hungry
right now, so let's say your experiment will examine four people's
ability to throw a ball when they haven't eaten for a specific period of time -
6, 12, 18 and 24 hours.
We can say that in your
experiment, you are going to do something and then see what happens to
other things. But, that sentence isn't very scientific. So, we're going to
learn some new words to replace the unscientific ones, so we can provide a
scientific explanation for what you're going to do in your
experiment.
The starting point here is
to identify what a variable is. A variable is
defined as anything that has a quantity or quality that varies. Your
experiment's variables are not eating and throwing a ball.
Now, let's science up that
earlier statement. 'You are going to manipulate a variable to see what happens to
another variable.' It still isn't quite right because we're using the blandest
term for variable, and we didn't differentiate between the
variables. Let's take a look at some other terms that will help us make this
statement more scientific and specific.
Dependent
and Independent Variables
A moment ago, we discussed
the two variables in our experiment - hunger and throwing a ball.
But, they are both better defined by the terms 'dependent' or
'independent' variable.
The dependent
variable is the variable a researcher is interested in.
The changes to the dependent variable are what the researcher is trying to
measure with all their fancy techniques. In our example, your dependent
variable is the person's ability to throw a ball. We're trying to measure the
change in ball throwing as influenced by hunger.
An independent
variable is a variable believed to affect the dependent variable.
This is the variable that you, the researcher, will manipulate to see
if it makes the dependent variable change. In our example of hungry people
throwing a ball, our independent variable is how long it's been since they've
eaten.
To reiterate, the independent
variable is the thing over which the researcher has control and is manipulating.
In this experiment, the researcher is controlling the food intake of the participant.
The dependent variable is believed to be dependent on the independent
variable.
Your experiment's dependent
variable is the ball throwing, which will hopefully change due to the
independent variable. So now, our scientific sentence is, 'You
are going to manipulate an independent variable to see what happens to the
dependent variable.'
Unwanted Influence
Sometimes, when you're
studying a dependent variable, your results don't make any sense. For instance,
what if people in one group are doing amazingly well while the other groups are
doing about the same. This could be caused by a confounding
variable, defined as an interference caused by another variable.
In our unusually competent group example, the confounding variable could
be that this group is made up of players from the baseball team.
In our original example of
hungry people throwing the ball, there are several confounding variables we
need to make sure we account for. Some examples would be:
- Metabolism and weight of the
individuals (for example, a 90 lb woman not eating for 24 hours compared
to a 350 lb man not eating for 6 hours)
- Ball size (people with smaller hands
may have a difficult time handling a large ball)
- Age (a 90-year-old person will
perform differently than a 19-year-old person)
Confounding variables are a
specific type of extraneous variable. Extraneous
variables are defined as any variable other than the independent and
dependent variable. So, a confounding variable is a variable that could
strongly influence your study, while extraneous variables are weaker and
typically influence your experiment in a lesser way. Some examples from our
ball throwing study include:
- Time of year
- Location of the experiment
- The person providing instructions
Our scientific sentence is
now, 'You're going to manipulate the independent variable to see what happens
to the dependent variable, controlling for confounding or extraneous
variables.'
Reducing or Increasing
Changes
In an experiment, if you
have multiple trials, you want to reduce the number of changes between each
trial. If you tell the ball throwers on the first day to toss
a ping-pong ball into a little red cup, and on the second day you tell ball
throwers to hurl a bowling ball into a barrel, your results are
going to be different.
Comments
Post a Comment