Data Analysis And Interpretation

By Author: Pierce Brosnan
Total Articles: 127
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Introduction to data analysis and interpretation:

For any research or for any project, after the required data are collected, the data are analyzed and interpreted.There several process while data are collected and analyzed and interpreted.this article is about data analysis and interpretation.

There are three objectives of the data analysis:

Getting a feel of the data,
validity and reliability and
Testing the hypothesis of the investigation
Data Analysis and Interpretation-1: Feel of the Data

All the data are listed and summarized.We use statistics to reduce the large data into meaning data showing central tendencies. There are three measures of central tendency – the mode, the medium and the mean. These three measures are designed to result a typical score.depending on the variety of distribution(normal and skewed) and level of measurements of varible,the mode of measurement is chosen.

For example,the per capita income of of Brunei is US$ 53,1000,It seems that everybody in Brunei is rich,but in reality it is not the case.there are poor people.using dispersion,deviation ...
... we can get to know how wealth are distributed.Using standard deviation we can figure out the rich and the poor percentages.

Data Analysis and Interpretation-2: Reliability & Validity

When performing data analysis and interpretation it is very important to make sure that the data collected are reliable and valid.Reliable data are trustworthy and can be dependable,while valid data are more genuine,appropriate and authenticated.So,while collecting data,reliability and validity should be given the ultimate priority,otherwise wrong data analysis will be performed.

Data Analysis and Interpretation.3.:hypotheses Testing

After being sure of reliability and validity of data,the researchers ove to the next stage-Hypothesis Testing.hypothesis testing is the process where researchers develop the thesis and test the measures using some standard formula.for example standar formula of standar deviation,sample mean etc.It determines whether the data analysis meets its requirement by using the gathered data and the measures.

NULL HYPOTHESIS: When hypothesis test does not meets its requirement it is called Null hypothesis.

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