Common data analysis methods
2024-10-22 16:17:54 0 Report
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This flowchart provides an overview of common data analysis methods, designed to simplify complex problems and enhance decision-making. It includes techniques like Logic Tree Analysis for problem simplification, PEST Analysis for industry insights, and multi-dimensional disassembly for diverse perspectives. Comparative analysis aids in understanding differences, while hypothesis testing explores causal relationships. Correlation analysis examines connections between variables. For user insights, methods like RFM Analysis and the AARRR Model are highlighted. Funnel analysis is used for transformation analysis, and DuPont analysis aids in financial evaluation. This comprehensive guide is essential for effective data-driven strategies.
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Outline/Content
Analysis Purpose
Analysis method
Concept Explanation
Simplify complex problems
Logic Tree Analysis Method
Industry Analysis
PEST Analysis
Think from multiple perspectives
Multi-dimensional disassembly analysis method
Multi-dimensional analysis method: Dimension + DisassemblyDimension: the angle from which to look at a problemDisassembly: breaking down a problem into indicators of different dimensions
Comparison
Comparative analysis method
How to analyze the causes
Hypothesis Testing Analysis Method
What is the relationship between A and B?
Correlation analysis
Correlation analysis method: Study the relationship between two or more data.
Retention and churn analysis
Group analysis method
User value classification
RFM Analysis
User behavior analysis
AARRR Model Analysis Method
Transformation analysis
Funnel analysis method
Funnel analysis is a method of analyzing things using a framework similar to a funnel. This method can characterize and analyze the state features of the research object
Financial Analysis
DuPont analysis
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