INI

Data Analysis Techniques - INI

Data analysis techniques are statistical and machine learning methods used to extract valuable insights from large datasets and support decision-making. Various techniques exist depending on the purpose, such as regression analysis, cluster analysis, and principal component analysis, applied for prediction, classification, segmentation, and dimensionality reduction. In the modern big data era, these techniques have become essential tools across all industries including marketing, healthcare, finance, and manufacturing.

data analysis statistics machine learning regression analysis cluster analysis principal component analysis data science predictive analytics

[item.regression-analysis]
code=01
slug=regression-analysis
name=Regression Analysis
description=A statistical method that models relationships between variables for prediction.
category=Predictive Analysis
learningType=supervised

[item.cluster-analysis]
code=02
slug=cluster-analysis
name=Cluster Analysis
description=An unsupervised learning method that groups data based on similarity.
category=Segmentation
learningType=unsupervised

[item.principal-component-analysis]
code=03
slug=principal-component-analysis
name=Principal Component Analysis
description=A dimensionality reduction technique that compresses high-dimensional data into lower dimensions.
category=Dimensionality Reduction
learningType=unsupervised

[item.factor-analysis]
code=04
slug=factor-analysis
name=Factor Analysis
description=A method that extracts latent factors underlying observed data.
category=Dimensionality Reduction
learningType=unsupervised

[item.discriminant-analysis]
code=05
slug=discriminant-analysis
name=Discriminant Analysis
description=A method that creates discriminant functions to classify data into groups.
category=Classification
learningType=supervised

[item.time-series-analysis]
code=06
slug=time-series-analysis
name=Time Series Analysis
description=A method that analyzes trends and periodicity in data along a time axis.
category=Predictive Analysis
learningType=supervised

[item.decision-tree-analysis]
code=07
slug=decision-tree-analysis
name=Decision Tree Analysis
description=A method that builds tree structures through conditional branching for classification and prediction.
category=Classification and Prediction
learningType=supervised

[item.association-analysis]
code=08
slug=association-analysis
name=Association Analysis
description=A method that discovers association rules between items.
category=Pattern Discovery
learningType=unsupervised

[item.correlation-analysis]
code=09
slug=correlation-analysis
name=Correlation Analysis
description=A method that measures the strength and direction of relationships between variables.
category=Relationship Analysis
learningType=unsupervised

[item.abc-analysis]
code=10
slug=abc-analysis
name=ABC Analysis
description=A method that classifies items into three groups based on importance.
category=Prioritization
learningType=unsupervised