The Data Analysis is the process by which we can extract the useful information and all is happen when we pass our data through many steps, the steps are these:-
-Inspecting the data.
-Cleaning the data.
-Transforming the data.
-And last modeling the data.
These four are the key characteristics of the data analysis. The data analysis is used for the decision making. The Algebra data analysis is also a same approach that contains the same procedure to analyze the data. It is only used when we have algebraic data, equations and formulas. The aim of data analysis is same in all scenarios. Data analysis has many facets, methods, procedures, approaches and techniques so that we can easily analyze the data. The most common and useful technique for the data analysis is data mining.
Sometimes the data analysis can be considered as the data modeling. Before data analyzing, we should be familiar with the types of data, data can be following types: -
Quantitative data: - It means those types of data that can be measured in terms of number.
Categorical data: - It means variety of data.
Qualitative data: - It means that data that has good features.
Let’s see the step by step process of data analysis: -
Data cleaning: - This is the first useful step; in this step we examine the data, if errors are there then resolve them. The process of data cleaning is made at the time of data entry. During the data cleaning we need to maintain both the types of data that is updated data and original data. After it all the alterations should be properly documented.
Initial data analysis: - This analysis includes the following steps, that are:-
i) Quality of data:- In this phase we check the quality of data by doing the several operation on the data such as analysis of missing observations, frequency counts, mean - median, extreme observations analysis and many more.
ii) Quality of measurements:- After checking the data quality we determine the ways of quality measurements that are confirmatory factor analysis and internal consistency analysis.
iii) Initial Transformations:- In this step we do the transform for the one or more variables and for this we have some transformation such as Square root, long and inverse transformations.
Main data analysis:- This is the final step of data analysis that also includes the some steps:-
i) Exploratory and confirmatory approaches:- The exploratory approaches does not deals with the no clear hypothesis, it only find the data for the models. And in confirmatory approaches or analysis we only include the clear hypothesis.
ii) Stability of results:- In this we check that our results are reliable or not? To specify this we use two methods that are cross validation and sensitivity analysis.
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