Statistical
Analysis
Statistical
analysis in research is a tool used for analyzing data. The whole method
consists of many steps including:
·
Planning
·
Designing
·
Data collection
·
Analysis
·
Interpretation
·
Report
Analyzing data statistically helps the researcher to elaborate his findings in a better
way. Statistics is a branch of science
that involves data collection, its organization and its evaluation and
interpretation. Many statistical tests are available for analyzing data.
However the researcher usually found it difficult to apply these methods for
his or her own good. Another important issue is that the researcher fails to
decide which method should be followed for his or her study. Consulting an
expert is not affordable for every researcher. In such circumstances the
researcher found statistical analysis as a nightmare, however there are some
important tips that can help the researcher to overcome such a difficult
situation.
Types
of Statistics
Before
discussing some useful tips let us shed some light on the basic types of
statistics. There are two basic types of Statistics:
·
Descriptive
·
Inferential
Descriptive
Statistics:
Descriptive
statistics draws a relationship between sample and population in the form of
mean, median and mode.
Inferential
Statistics:
In
inferential statistics data is collected randomly. It is useful in such a
situation when it is difficult to consider each individual of a population for
examination.
Tips
for Statistical Analysis
An
increase has been observed in the use statistical methods in every field of
research. Below are mentioned a number of tips that can help the researcher to
utilize statistical methods in a better way:
1. First
of all analyze the nature of the data to be analyzed statistically should be
described clearly.
2.
The next step is to find out the
relation between the data and the population of the study.
3.
Draw a model that would relate the
relation between the data and the underlying population.
4.
Try to find out the validity of the
data.
5. Through
use of predictive analytics find out the future scenario of the data
Some
Most Common Methods for Statistical Analysis
The
five basic fundamental tools for data analysis are as follows:
1. Mean
Mean most commonly used as average is
used to determine the overall trend of the data. It is helpful in finding out
quick results however the accuracy of its results is doubtful sometimes.
2.
Standard Deviation
It is represented with a Greek symbol ∑.
It signifies that data is more widely spread with the mean. It is helpful in
finding out the dispersion points of the data. However it might prove deceptive
in many cases.
3.
Regression
Regression represents the strength of
dependent and explanatory variables. It is used to find out the trends of
different application. However sometimes the regression may manipulate the
results on the outliers.
4.
Sample Size Determination
With the help of proportions and
standard deviation methods it is easier to find out the accurate sample size. However
due to interference of untested variable the validity of data can be
challenged.
5.
Hypothesis Testing
It is also called as t Testing. It is used in every
field study including business, science and economics etc.
