A lie can travel the whole world By Prof Dr Sohail ansari & Variables 7
A funeral
passed by the Prophet (PBUM), and he stood up. It was said to him, “It is a
Jew.” The Prophet said, “Was he not a soul?”
Ṣaḥīḥ al-Bukhārī 1250Every man wants a woman to appeal to his better
side, his nobler instincts, and his higher nature - and another woman to help
him forget them. Helen Rowland
Truth is to be denied for a lie to be untrammeled
·
A lie can travel as well other halfway around
the world if truth is denied the shoes. Ingenuity in creating the straitjacket
of censorship ensures dangerous watchdogs are muzzled.
· “A lie can travel
halfway around the world while the truth is putting on its shoes.” » Mark Twain
Variables in research
When doing social research, variables are
both important and tricky. Here's a few words about them.
Definitions
A variable is something
that can change, such as 'gender' and are typically the focus of a study.
Attributes are
sub-values of a variable, such as 'male' and 'female'. (Sub means under or below) An exhaustive list
contains all possible answers, for example gender could also include 'male
transgender' and 'female transgender' (and both can be pre- or post-operative).
Mutually
exclusive attributes are
those that cannot occur at the same time. Thus in a survey a person may be
requested to select one answer from a list of alternatives (as
opposed to selecting as many that might apply).
Quantitative data is
numeric (relating to or expressed as a number or numbers).This is useful for
mathematical and statistical analysis that leads to a predictive
formula.
Qualitative data is
based on human judgment. You can turn qualitative data into quantitative data, for
example by counting the proportion of people who hold a particular
qualitative viewpoint.
Units are the
ways that variables are classified. These include: individuals, groups,
social interactions and objects.
Types
Descriptive variables are
those that which will be reported on, without relating them
to anything in particular.
Categorical variables result
from a selection from categories, such as 'agree' and 'disagree'. Nominal
and ordinal variables are categorical.
Numeric variables give a
number, such as age.
Discrete variables are
numeric variables that come from a limited set of numbers. They may result from
, answering questions such as 'how many', 'how often', etc.
Continuous variables are
numeric variables that can take any value, such as weight.
Independence
An independent variable is
one is manipulated by the researcher. It is like the knob on a dial that the
researcher turns. In graphs, it is put on the X-axis.
A dependent variable is
one which changes as a result of the independent variable being changed, and is
put on the Y-axis in graphs.
The holy grail for researchers is to be
able to determine the relationship between the independent and dependent
variables, such that if the independent variable is changed, then the
researcher will be able to accurately predict how the dependent variable will
change.
Extraneous variables are
additional variables which could provide alternative explanations or
cast doubt on conclusions.
Variables may have the following characteristics:
·
Period: When it starts and stops.
·
Pattern: Daily, weekly, ad-hoc, etc.
·
Detail: Overview through to 'in depth'.
·
Latency: Time between measuring dependent and independent
variable (some things take time to take effect).
Control
Note that in an experiment there may be
many additional variables beyond the manipulated independent variable and the
measured dependent variables. It is critical in experiments that these variables
do not vary and hence bias or otherwise distort the
results. There is a struggle between control
vs. authenticity in managing this.
Correlation
With perfect correlation, the X-Y graph of
points (as a scatter
diagram) will give a straight line. Whilst this may happen in physics,
it seldom happens in social research and a probabilistic relationship is the
best that can be determined.
Correlation can be positive (increasing
X increases Y), negative (increasing X decreases Y) or non-linear (increasing X
makes Y increase or decrease, depending on the value of X).
Correlation can also be partial, that is
across only a range of values X. As all possible values of X can seldom be
tested, most correlations found are at best partial.
Cause
When correlation is determined, a further
question is whether varying the independent variable caused the
independent variable to change. This adds complexity and debate
to the situation.
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