outcomes, or as unions, Contrast objects. intersections or Distal Precursor: complements of other Classify. events. Proximal Precursor: Recognize possible outcomes. G.CP.A.2 Understand the definition of Explain simple events. independent events and use Recognize impossible outcomes. it to solve problems. Target: G.CP.A.3 Calculate conditional Determine if 2 events are independent probabilities of events. or dependent. G.CP.A.4 Construct and interpret Successor: frequency tables of Explain compound events. data when two categories are associated with each object being classified. Use the two-way table as a sample space to decide if events are independent and to approximate conditional probabilities. G.CP.A.5 Recognize and explain the concepts of conditional probability and independence in a context. G.CP.A.6 and interpret the Not Not applicable. Not applicable. Addition Rule for calculating applicable. probabilities. G.CP.A.7 Apply and interpret the Not Not applicable. Not applicable. general Multiplication Rule applicable. in a uniform probability model.
outcomes, or as unions, intersections or complements of other events. Contrast objects. Distal Precursor: Classify. Proximal Precursor: Recognize possible outcomes. Explain simple events. Recognize impossible outcomes. Target: Determine if 2 events are independent or dependent. Successor: Explain compound events. G.CP.A.2 Understand the definition of independent events and use it to solve problems. G.CP.A.3 Calculate conditional probabilities of events. G.CP.A.4 Construct and interpret frequency tables of data when two categories are associated with each object being classified. Use the two-way table as a sample space to decide if events are independent and to approximate conditional probabilities. G.CP.A.5 Recognize and explain the concepts of conditional probability and independence in a context. G.CP.A.6 and interpret the Addition Rule for calculating probabilities. Not applicable. Not applicable. Not applicable. G.CP.A.7 Apply and interpret the general Multiplication Rule in a uniform probability model. Not applicable. Not applicable. Not applicable.
curr-mapa-math-k-12-crosswalk.docx