Computer Science & IT
Types of Data Analysis: Methods and Techniques
The data analysis process mainly involves cleaning, transforming, and modeling/visualizing data to produce accurate results for business purposes. Data Analysis is classified into several types:
- Descriptive analysis: It is also known as Statistical analysis, and it describes the statistical techniques used in the data set. For example, Keeping track of a student’s progress using online learning grade systems.
- Predictive analysis: Analyze the data for future use based on the report or cleansed dataset. It is based on the organization’s previous outcomes and predicts future inputs and outcomes.
- Inferential analysis: Determines the population by obtaining random results from a set of samples. The primary examples of inferential analysis are ANOVA and the T Test.
- Exploratory analysis: Using all of the preceding methods, finally, EDA is completed by all of the preprocessing requirements. To manipulate a large number of data sets, EDA will be used. EDA examples include block graphs and line graphs.
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Reference:
https://doi.org/10.1002/mas.21602
Verbeeck, N., Caprioli, R. M., & Van de Plas, R. (2020). Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry. Mass spectrometry reviews, 39(3), 245-291.