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Question 812

Which of the following analytical methods would be MOST useful when trying to identify groups with similar behavior or characteristics in a large population?

    Correct Answer: D

    The most useful analytical method for identifying groups with similar behavior or characteristics in a large population is classification. Classification involves categorizing data into predefined classes or groups based on their attributes. It is a form of supervised learning used to segment data into distinct groups that share common characteristics, making it highly effective for analyzing large datasets and identifying patterns.

Discussion
SibsankarOption: D

Classification involves categorizing data into predefined classes or groups based on their attributes. It is highly effective in analyzing large datasets to identify and segment groups with similar behaviors or characteristics. While clustering (which is a type of unsupervised learning) is often the preferred method for discovering natural groupings within a dataset, classification (a type of supervised learning) is also a powerful tool when the categories or groups are already known. D is 100% answer here

SwallowsOption: B

Sampling that identifies groups with similar behaviors and characteristics in a large population is called clustering.

3008Option: B

clustering analysis is to group similar objects by static classification method

mekuskyOption: B

Should be B

KAP2HURUFOption: D

Cluster sampling is a statistical method used for selecting a random sample of clusters from a population for the purpose of conducting a survey or study. It is not an analytical method for identifying groups with similar characteristics; rather, it is a sampling technique.

SuperMaxOption: C

B. Cluster sampling Cluster sampling is a method of sampling where the population is divided into clusters or groups, and then a random sample of clusters is selected for further analysis. Within each selected cluster, all individuals or a subset of individuals are included in the study. This approach is particularly effective when you want to identify groups with similar behavior or characteristics because it naturally groups individuals who are geographically or demographically close together. This allows for the identification of patterns and similarities within these clusters, making it a valuable method for analyzing large populations and finding groups with common traits or behaviors. The other options, while important in various analytical contexts, may not be as directly suited for identifying groups with similar behavior or characteristics within a large population