Page 76 - The Ontario Curriculum, Grades 11 and 12: Mathematics, 2007

Grade 1G1ra, dUen1i1v,erCsoitllye/gCeoPllregpearParteiopnaration
1. solve problems involving one-variable data by collecting, organizing, analysing, and evaluating data; 2. determine and represent probability, and identify and interpret its applications.
THE ONTARIO CURRICULUM, GRADES 11 AND 12 | Mathematics
74
By the end of this course, students will:
SPECIFIC EXPECTATIONS
1. Working With One-Variable Data
By the end of this course, students will:
1.1 identify situations involving one-variable data (i.e., data about the frequency of a given occurrence), and design questionnaires (e.g., for a store to determine which CDs to stock, for a radio station to choose which music to play) or experiments (e.g., counting, taking measurements) for gathering one-variable data, giving consideration to ethics, privacy, the need for honest responses, and possible sources of bias
Sample problem: One lane of a three-lane highway is being restricted to vehicles with at least two passengers to reduce traffic congestion. Design an experiment to collect one-variable data to decide whether traffic congestion is actually reduced.
1.2 collect one-variable data from secondary sources (e.g., Internet databases), and organ- ize and store the data using a variety of tools (e.g., spreadsheets, dynamic statistical software)
1.3 explain the distinction between the terms population and sample, describe the charac-
teristics of a good sample, and explain why sampling is necessary (e.g., time, cost, or physical constraints)
Sample problem: Explain the terms sample and population by giving examples within your school and your community.
1.4 describe and compare sampling techniques (e.g., random, stratified, clustered, conven- ience, voluntary); collect one-variable data from primary sources, using appropriate sampling techniques in a variety of real-world situations; and organize and store the data
1.5 identify different types of one-variable data (i.e., categorical, discrete, continuous), and represent the data, with and without techno- logy, in appropriate graphical forms (e.g., histograms, bar graphs, circle graphs, pictographs)
1.6 identify and describe properties associated with common distributions of data (e.g., normal, bimodal, skewed)
1.7 calculate, using formulas and/or technology (e.g., dynamic statistical software, spread- sheet, graphing calculator), and interpret measures of central tendency (i.e., mean, median, mode) and measures of spread
(i.e., range, standard deviation)
1.8 explain the appropriate use of measures
of central tendency (i.e., mean, median, mode) and measures of spread (i.e., range, standard deviation)
Sample problem: Explain whether the mean or the median of your course marks would be the more appropriate representation of your achievement. Describe the additional information that the standard deviation
of your course marks would provide.
1.9 compare two or more sets of one-variable data, using measures of central tendency and measures of spread
Sample problem: Use measures of central tendency and measures of spread to compare data that show the lifetime of an economy light bulb with data that show the lifetime of a long-life light bulb.
1.10 solve problems by interpreting and analysing one-variable data collected from secondary sources
D. DATA MANAGEMENT OVERALL EXPECTATIONS