Density-based Clustering
Advanced Statistical Analysis Techniques in Business
Machine Learning Techniques for Data Cleaning
Understanding Data Patterns and Trends
Methods
Analyzing Survey Responses
Techniques for Analyzing Customer Conversations
Key Components of Data Analysis Frameworks
Statistical Analysis Strategies 
K-Means
Clustering: Partitions data into K distinct clusters
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Advanced Statistical Analysis Techniques in Business Methods of Cluster Analysis Method Description K-Means
Clustering Partitions data into K distinct clusters based on distance from the centroid
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Machine Learning Techniques for Data Cleaning Clustering Algorithms: Grouping similar records together to identify duplicates
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Understanding Data Patterns and Trends Some common algorithms include:
Clustering: Groups similar data points together
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Methods Technique Description Applications
Clustering Grouping similar data points together based on their characteristics
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Analyzing Survey Responses Common techniques include:
Clustering: Group similar responses together to identify distinct segments
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Techniques for Analyzing Customer Conversations Clustering: Grouping customers based on similarities in their conversations to tailor marketing strategies
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Key Components of Data Analysis Frameworks Clustering: Grouping similar data points based on characteristics
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How to Interpret Results 2 Case Study 2: Customer Segmentation A telecommunications firm applied
clustering algorithms to segment customers based on usage patterns
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