# Types of Analysis

Causal

n. a method of searching for the cause or causes of certain effects. Because the causal factor needs to be identified, the researcher will have to obtain data or use inferences. When data cannot be obtained through experimentation, the causal inference must be dependable and justifiable.

Causal

Causal Analysis seeks to identify and understand the reasons why things are as they are and hence enabling focus of change activity. Root causes. The basic principle of causal analysis is to find causes that you can treat rather than treating symptoms (which, as all doctors know, seldom effects a lasting cure).

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Descriptive

Descriptive statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures. Together with simple graphics analysis, they form the basis of virtually every quantitative analysis of data.

Exploratory

In statistics, exploratory data analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis testing task.

Inferential

Inferential analysis uses statistical tests to see whether a pattern we observe is due to chance or due to the program or intervention effects. Research often uses inferential analysis to determine if there is a relationship between an intervention and an outcome as well as the strength of that relationship.

source: cyfar.org
Mechanistic

It's not a common term, as far as I can tell, but it refers to the study of deterministic systems. That is, phenomena which are entirely determined by well defined mechanisms, as opposed to phenomena which are defined by imperfect representations.

source: quora.com
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Mechanistic

It's not a common term, as far as I can tell, but it refers to the study of deterministic systems. That is, phenomena which are entirely determined by well defined mechanisms, as opposed to phenomena which are defined by imperfect representations.

source: quora.com
Predictive

Predictive analytics enables organizations to function more efficiently. Reducing risk. Credit scores are used to assess a buyerâ€™s likelihood of default for purchases and are a well-known example of predictive analytics.

source: sas.com
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