Explain the difference between secondary and primary data. Give an e.pdf

Explain the difference between qualitative, quantitative, discrete, and continuous variables.
Solution
Discrete variables are also called categorical variables. A discrete variable, X, can
take on a finite number of numerical values, categories or codes. Discrete variables can be
classified into the following categories: Nominal variables Ordinal variables Dummy variables
from quantitative variables Preference variables Multiple response variables Continuous
variables can be classified into three categories: Interval - scale Variables: Interval scale data
has order and equal intervals. Interval scale variables are measured on a linear scale, and can take
on positive or negative values. It is assumed that the intervals keep the same importance
throughout the scale. They allow us not only to rank order the items that are measured but also to
quantify and compare the magnitudes of differences between them. We can say that the
temperature of 40°C is higher than 30°C, and an increase from 20°C to 40°C is twice as much as
the increase from 30°C to 40°C. Counts are interval scale measurements, such as counts of
publications or citations, years of education, etc. Continuous Ordinal Variables They occur
when the measurements are continuous, but one is not certain whether they are on a linear scale,
the only trustworthy information being the rank order of the observations. For example, if a scale
is transformed by an exponential, logarithmic or any other nonlinear monotonic transformation,
it loses its interval - scale property. Here, it would be expedient to replace the observations by
their ranks. Ratio - scale Variables These are continuous positive measurements on a nonlinear
scale. A typical example is the growth of bacterial population (say, with a growth function
AeBt.). In this model, equal time intervals multiply the population by the same ratio. (Hence, the
name ratio - scale). Ratio data are also interval data, but they are not measured on a linear scale.
. With interval data, one can perform logical operations, add, and subtract, but one cannot
multiply or divide. For instance, if a liquid is at 40 degrees and we add 10 degrees, it will be 50
degrees. However, a liquid at 40 degrees does not have twice the temperature of a liquid at 20
degrees because 0 degrees does not represent \"no temperature\" -- to multiply or divide in this
way we would have to use the Kelvin temperature scale, with a true zero point (0 degrees Kelvin
= -273.15 degrees Celsius). In social sciences, the issue of \"true zero\" rarely arises, but one
should be aware of the statistical issues involved..

1. Explain the difference between secondary and primary data. Give an example of each.

Solution

There are various methods of classifying data.
A general classification is based on who collected the data.
Primary data: Primary data are first hand information. This information is collected directly from
the source by means of field studies. Primary data are original and are like raw materials. It is the
crudest form of information. The investigator himself collects primary data or supervises its
collection. It may be collected on a sample or census basis or from case studies..
Examples: Data gathered by a student for their thesis or research project.
Secondary data: Secondary data are the Second hand information. The data which have already
been collected and processed by some agency or persons and are not used for the first time are
termed as secondary data. According to M. M. Blair,