W#14 8 Clusters

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What is a cluster in the context of data analysis?

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A cluster is a group of data points that are more similar to each other than to those in other groups, often identified in scatter plots.

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CCSS.8.SP.A.1

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How can you visually identify clusters in a scatter plot?

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Clusters can be visually identified by looking for groups of points that are close together, separated from other groups of points.

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CCSS.8.SP.A.1

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What does it mean if a scatter plot has one cluster?

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It means that the data points are closely grouped together, indicating a single pattern or trend in the data.

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CCSS.8.SP.A.1

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What does it mean if a scatter plot has multiple clusters?

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It indicates that there are distinct groups within the data that may represent different patterns or categories.

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CCSS.8.SP.A.1

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What is the significance of identifying clusters in data analysis?

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Identifying clusters helps in understanding the structure of the data, revealing patterns, and making predictions.

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What are some common methods for clustering data?

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Common methods include K-means clustering, hierarchical clustering, and DBSCAN.

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CCSS.HSS.ID.B.5

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What is K-means clustering?

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K-means clustering is a method that partitions data into K distinct clusters based on distance to the centroid of each cluster.

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CCSS.HSS.IC.B.3

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What is the role of the centroid in K-means clustering?

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The centroid is the center point of a cluster, calculated as the mean of all points in that cluster.

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CCSS.6.SP.A.3

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How do you determine the optimal number of clusters in K-means?

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The optimal number of clusters can be determined using methods like the elbow method or silhouette analysis.

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What is the elbow method in clustering?

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The elbow method involves plotting the explained variance as a function of the number of clusters and looking for a 'knee' point where the rate of improvement decreases.