Computer Science Standards
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        Standard Identifier: 9-12S.DA.8
                    Grade Range:
                    
                        9–12 Specialty
                    
                
            
                        Concept:
                        
                            Data & Analysis
                        
                    
                    
                        Subconcept:
                        
                            Collection, Visualization, & Transformation
                        
                    
            
                        Practice(s):
                        
                            Developing and Using Abstractions, Communicating About Computing (4.1, 7.1)
                        
                    
            Standard:
Use data analysis tools and techniques to identify patterns in data representing complex systems.
Descriptive Statement:
Data analysis tools can be useful for identifying patterns in large amounts of data in many different fields. Computers can help with the processing of extremely large sets of data making very complex systems manageable. Students use computational tools to analyze, summarize, and visualize a large set of data. For example, students could analyze a data set containing marathon times and determine how age, gender, weather, and course features correlate with running times. Alternatively, students could analyze a data set of social media interactions to identify the most influential users and visualize the intersections between different social groups.
                Use data analysis tools and techniques to identify patterns in data representing complex systems.
Descriptive Statement:
Data analysis tools can be useful for identifying patterns in large amounts of data in many different fields. Computers can help with the processing of extremely large sets of data making very complex systems manageable. Students use computational tools to analyze, summarize, and visualize a large set of data. For example, students could analyze a data set containing marathon times and determine how age, gender, weather, and course features correlate with running times. Alternatively, students could analyze a data set of social media interactions to identify the most influential users and visualize the intersections between different social groups.
        Showing 11 - 11 of 11 Standards
    
        
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