Data Analysis Methods and Techniques

- Overview

Data analysis has two main methods: qualitative research and quantitative research. Each method has its own techniques:

• Qualitative research: Involves working with unique identifiers, such as labels and properties, and categorical variables, such as statistics, percentages, and measurements. A data analyst may use firsthand or participant observation approaches, conduct interviews, run focus groups, or review documents.
• Quantitative research: Involves data expressed in numbers of numerical figures. This type of data can be distinguished into categories, grouped, measured, calculated, or ranked. Experiments and surveys are quantitative research.

There are eight types of data analysis: descriptive, diagnostic, exploratory, inferential, predictive, causal, Mechanistic, prescriptive. 

Here are some data analysis methods and techniques:

• Regression analysis: A popular method that uses a supervised machine learning (ML) algorithm to identify relationships between variables.
• Time series analysis: A technique for analyzing time-series data, which is data in a series of specific time intervals.
• Qualitative analysis: A creative, dynamic, and intuitive process of inductive reasoning, theorizing, and thinking.
• Descriptive analysis: A technique that uses mathematical aspects like percentages, frequencies, and central tendencies to find patterns in data.
• Cluster analysis: A technique for exploratory studies that assigns different types of entities to groups with similar characteristics.
• Exploratory data analysis: A data mining methodology that involves reviewing datasets to highlight their key features. EDA focuses on probing facts objectively without any expectations.
• Factor analysis: A technique that helps find the underlying structure in a set of variables. It helps find independent variables in the data set that describe patterns and models of relationships.
• Machine learning: A method of data analysis that automates analytical model building. It is a branch of technology that allows systems to learn from data, identify patterns, and make decisions with minimal human intervention.
• Monte Carlo method: A technique used in cases where there's an intervention of random variables. It was invented during World War II to improve decision-making under highly uncertain conditions.