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Exploratory and Confirmatory Data Analysis

The multidimensional data analysis is used for forecasting models, as predictions are allowed to be made for numerous timelines, which were created by a number of forecasters, and made in numerous horizons. But social research will deal with quite a bit of hypothesis testing. It is understandable because human beings change behaviors and moods constantly. Tools have to be developed that can review ideas to determine their overall value in extracting information. Confirmatory factor analysis is one such instrument.

statistical data analysis schema

Confirmatory Data Analysis Definition

Talking about the confirmatory data analysis definition, simply put, confirmatory factor analysis is going to test a hypothesis, and generate an estimate. Examples of this type of analysis include analysis of variance and regression analysis. What is important is that confirmatory data analysis needs a hypothesis to examine and evaluate.

Exploratory data analysis is a shade different. This form of analysis suggests a hypothesis. Exploratory data analysis will make use of descriptive statistics with reliance on having the data alone formulate questions. Confirmatory data analysis will employ inferential statistics and will use probability models.

Confirmatory Data Analysis versus Exploratory Data Analysis

Both are tools that have advantages and drawbacks in their approach to looking at data. Confirmatory data analysis works with theories and methods that are firmly established. There is an emphasis on numerical calculation, but it provides precise information. Exploratory analysis will not ask for more than what can be supported by data and is very flexible it comes to creating a hypothesis.

A trouble that confirmatory data analysis will run into is that preconceived ideas will be the focus of the analysis and it may be hard to recognize results that are not expected. Exploratory data analysis will often not provide solid answers. These pluses and minuses of both forms can lead to some confusion as to which should be used in a given situation. If you are a bit overwhelmed and feel like committing the fulfillment of your task to a specialist, don’t doubt to trust statistical analysis services in Canada. Our professionalists will do the best for you!

Which to Use?

The answer is elementary, my dear Watson. Use both, but in the right sequence. This is an exercise in thinking about statistics. Exploratory data analysis is exactly that: it seeks. As it looks through the information, the tools of expiratory data analysis begin to generate questions and hypothesis that need explanation. Regression analysis is much simpler to do if a good hypothesis has been uncovered beforehand. Confirmatory data analysis then goes to work and does its magic. Because the hypothesis is already been uncovered, the expense of any experimentation is much lower. The calculation work that is so much a part of confirmatory data analysis is now brought to its full optimization. It would be different if the hypothesis was not created first. Exploratory data analysis sets the stage, confirmatory data analysis does the act. The two can work together to advance the knowledge.

There is a certain elegance to this relationship. It turns analysis into a thought process as opposed to just a digging up the data exercise. It creates the steps and process necessary to reach a final conclusion. Exploratory data analysis followed by confirmatory data analysis takes the solid benefits of both to generate an optimal end result. The strengths of either negate the deficiencies of either in the entire process. Suffice it to say that working together neither one is better than the other. They both form a relationship that can be extremely beneficial to social research work.

Learn everything about confirmatory data analysis and start using it in your research!