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.