In research
there are six tools, one being measurement. What exactly is measurement? When
we hear the word ‘measurement’, our mind automatically thinks of it as the
process of finding a number to show the size, length or the amount of something
by the use of a ruler or such mathematical instruments. However, that’s not the
concept to be discussed. Measurement in Research is putting a limit to a
specified period in which you want to study; for example, conducting a research
to show the different races and living styles in a community. Instead of having
a community grouping to try to head count and categorize the different races,
you could easily conduct a questionnaire/ survey. By doing so it will be easier
to attain a quantitative data. Measuring data can be either substantial– have
physical substance/ appearance in the world– or insubstantial – feelings,
thoughts, concepts.

There are four
Scales of Measurements in Research: nominal, ordinal, interval and ratio
scales. Nominal scale basically categorizes a group of objects using names to
show that one object differs from the other. For example, categorize a group of
Standard Six students by their hair colour. Data obtained does not overlap nor
does it have a numerical significance. Secondly, ordinal scale shows that one
object is bigger or better than another. For example, conducting a survey to
show how students feel about the school cafeteria. We may label the score sheet
with #1 being the worst, #2 being fairly good, #3 being good and #4 being
excellent. We can’t say how much worst is from fairly good. Ordinal scale only
measures feelings rather than numerical data. Interval scales not only measures
order, but also give a numerical difference between objects. For example, we
can measure the exact amount of time it takes two people walking the same
distance at different speed.  Lastly,
ratio scale tells the exact value of how many more times an object is bigger
than the other. For example, the difference between a height of ten feet and eight
feet is the same as the interval between five feet and three feet.

When a
researcher wants to know how good they’re measurements are they depend on
reliability and validity of measurements. The reliability is the consistency of
the measures taken by the researcher. The validity is where the results of the
measures represent what they are intended to. However, both validity and
reliability also shows the errors in our measurements. For example, if your mom
is making cake and is measuring the flour to make separate mixes, she won’t
always have the same exact measurement both times. Therefore, when conducting
research you must always be consistent with your measurements to get your
intended outcome.

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It is important
to understand the level of measurement of variables in research, because the
level of measurement tells the researcher what type of statistical analysis
should be done that will therefore draw a conclusion from the research.  Without measurement, the researcher fails to
interpret data accurately. Measurement in research is more than placing a
measuring tape to measure an object. It is to analyze and interpret data so
that researchers can find the answer to why an object behaves the way it does
for example.

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