There exist four forms of data analysis implemented across all sectors. Whereas these are separated into categories, these are built upon each other and linked together. While you begin moving from the most straightforward style of analytics forward, the level of difficulty and resources also hikes. Similarly, the level of added insight and value also rises. The four types of data analysis include:
- Predictive analysis– attempts to answer the question of what is likely to happen.
- Prescriptive analysis– this merges the insight from the past reviews and in determining the actions taken in solving a current problem and formulating a decision.
- Descriptive analysis– this an analysis that gives answers to the “what happened” by summarizing past data, usually in the form of dashboards’
- Diagnostic analysis– answers the “why did it happen?” that builds off descriptive analysis.
What are the methods of data analysis?
There are numerous methods used in analyzing data, all of which fall under two primary approaches that include quantitative analysis and qualitative data analysis.
Qualitative data analysis
The data obtained through this method consist of pictures, words, observations, and symbols. The following type of analysis infers to a process utilized for the data analysis and to provide some level of understanding, interpretation, or understanding. This type of data can be collected in numerous approaches, such as:
- Content analysis – this used to analyze behavioral or verbal data; this data consists of communication artifacts or documents in various formats, audio, or pictures.
- Narrative analysis – this majorly implemented, and it involves data from numerous sources such as surveys, field notes, and interviews. This includes reformulating the stories issued by individuals, depending on one’s experiences and variance in context.
- Grounded theory – this a form of analysis that is majorly implemented by researchers; this includes the creation of causal explanations of the single occurrence from the study of one or more cases. In further conducting the research, an example is altered until the researchers arrive at a statement that brings together all the circumstances.
This used for the qualification of data, which enables the generalization of the results obtained from a sample to a population’s interest. Some of the methodologies that fall under quantitative data include:
- Mean – also identified as the average, mean is the most common method of analyzing data whereby the sum of the lists of the number is divided by the number of items in the same list.
- Hypothesis testing – this mainly used in business research and is done to assess whether a given hypothesis or theory for a population or data set is precise.
- Sample size determination – when researching a large population, small sample-sized is taken into consideration, analyzed, and the results considered almost the same for every member of the community.