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The included tables map spring administrations from 2006 to 2011 to knowledge, thinking, and application codes, plus grade-level progressions for data collection and 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 \nGRADE SIX EQAO QUESTIONS: Data Management and Probability  \nOverall Expectations  \n\n| DV1 | • Collect and organize discrete or continuous primary data and secondary data and display the data using charts and graphs, including continuous line graphs |\n| --- | --- |\n| DV2 | • Read, describe, and interpret data, and explain relationships between sets of data |\n| DV3 | • Determine the theoretical probability of an outcome in a probability experiment, and use it to predict the frequency of the outcome |\n\n\n| Year | DV1 | DV2 | DV3 |\n| --- | --- | --- | --- |\n| Spring 2006 | MC26\u003Cbr>OR27 | MC6\u003Cbr>MC12 | MC13\u003Cbr>MC36\u003Cbr>OR10 |\n| Spring 2007 | MC26 | MC12\u003Cbr>MC32\u003Cbr>OR28 | MC11\u003Cbr>MC33\u003Cbr>OR7 |\n| Spring 2008 | MC13 | MC11\u003Cbr>MC36\u003Cbr>OR29 | MC12\u003Cbr>MC35\u003Cbr>OR9 |\n| Spring 2009 | OR27 | MC11\u003Cbr>MC13\u003Cbr>MC36 | MC12\u003Cbr>MC35\u003Cbr>OR8 |\n| Spring 2010 |  | MC11\u003Cbr>MC13\u003Cbr>MC36\u003Cbr>OR9 | MC12\u003Cbr>MC35\u003Cbr>OR27 |\n| Spring 2011 | MC18\u003Cbr>OR26 | MC4\u003Cbr>MC12 | MC21\u003Cbr>MC32\u003Cbr>OR9 |\n\nGRADE SIX EQAO QUESTIONS: Data Management and Probability  \n\n| Year | Knowledge & Understanding | Problem Solving\u003Cbr>(Thinking) | Application |\n| --- | --- | --- | --- |\n| Spring 2009 | MC36 | MC35\u003Cbr>OR8\u003Cbr>OR27 | MC11\u003Cbr>MC12\u003Cbr>MC13 |\n| Spring 2010 | MC36 | MC35\u003Cbr>OR9\u003Cbr>OR27 | MC11\u003Cbr>MC12\u003Cbr>MC13 |\n| Spring 2011 | MC12 | MC21 | MC4\u003Cbr>MC18\u003Cbr>MC32\u003Cbr>OR9\u003Cbr>OR26 |\n\nDATA MANAGEMENT & PROBABILITY: Collection and Organization of Data  \n\n| Grade 4 | Grade 5 | Grade 6 |\n| --- | --- | --- |\n| Overall Expectation |  |  |\n| -collect and organize discrete primary data and display the data using charts and graphs, including stem-and-leaf plots and double bar graphs | -collect and organize discrete or continuous primary data and secondary data and display the data using charts and graphs, including broken-line graphs | -collect and organize discrete or continuous primary data and secondary data and display the data using charts and graphs, including continuous line graphs |\n| Specific Expectations |  |  |\n|  | – distinguish between discrete data (i.e., data organized using numbers that have gaps between them, such as whole numbers, and often used to represent a count, such as the number of times a word is used) and continuous data (i.e., data organized using all numbers on a number line that fall within the range of the data, and used to represent measurements such as heights or ages of trees) |  |\n| -collect data by conducting a survey or an experiment to do with themselves, their environment, issues in their school or the community, or content from another subject, and record observations or measurements | -collect data by conducting a survey or an experiment do with themselves, their environment, issues in their school or community, or content from another subject, and record observations or measurements | -collect data by conducting a survey or an experiment to do with themselves, their environment, issues in their school or community, or content from another subject, and record observations or measurements |\n| -collect and organize discrete primary data and display the data in charts, tables, and graphs (including stem-and-leaf plots and double bar graphs) that have appropriate titles, labels, and scales that suit the range and distribution of the data, using a variety of tools | -collect and organize discrete or continuous primary data and secondary data and display the data in charts, tables, and graphs (including broken-line graphs) that have appropriate titles, labels and scales that suit the range and distribution of the data using a variety of tools | -collect and organize discrete or continuous primary data and secondary data and display the data in charts, tables, and graphs (including continuous line graphs) that have appropriate titles, labels, and scales that suit the range and distribution of the data, using a variety of tools |\n|  | -demon","cbCaisZyKqWtHFMn","https://ap.wps.com/l/cbCaisZyKqWtHFMn","pdf",6402369,43,"English","# Overall Expectations\n# Data Management & Probability: Collection and Organization of Data\n## Grade 4, Grade 5, Grade 6 Expectations\n# Data Management & Probability: Data Relationships\n## Grade 4, Grade 5, Grade 6 Expectations\n# Spring Year Code Tables (2006-2011)","[{\"question\":\"What overall skills are emphasized in Grade 6 EQAO Data Management and Probability?\",\"answer\":\"Students collect and organize data and display it using charts and graphs, read and interpret data to explain relationships, and determine theoretical probability to predict outcome frequency in experiments.\"},{\"question\":\"How does the document define discrete versus continuous data?\",\"answer\":\"Discrete data uses numbers with gaps (often counts), while continuous data uses all numbers on a number line within a measured range (often measurements like heights or ages).\"},{\"question\":\"What kinds of graphs and visual tools are referenced for Grade 6?\",\"answer\":\"The document highlights charts and graphs such as stem-and-leaf plots, bar graphs, broken-line graphs, and continuous line graphs, including the use of technology to graph data and justify graph choices.\"}]","Consolidation of Grade 6 EQAO Questions - Data Management and Probability | PDF",1790764795,108]