Ontario Curriculum

A.1.1: construct tables of values and graph quadratic relations arising from real-world applications (e.g., dropping a ball from a given height; varying the edge length of a cube and observing the effect on the surface area of the cube)

Addition and Subtraction of Functions

Quadratics in Polynomial Form

A.1.3: determine, through investigation using technology, the roles of a, h, and k in quadratic relations of the form y = a(x – h)² + k, and describe these roles in terms of transformations on the graph of y = x² (i.e., translations; reflections in the x-axis; vertical stretches and compressions to and from the x-axis)

Exponential Functions

Quadratics in Vertex Form

Translations

Zap It! Game

A.1.4: sketch graphs of quadratic relations represented by the equation y = a(x – h)² + k (e.g., using the vertex and at least one point on each side of the vertex; applying one or more transformations to the graph of y = x²)

A.1.7: factor trinomials of the form ax² + bx + c , where a = 1 or where a is the common factor, by various methods

A.1.9: solve problems, using an appropriate strategy (i.e., factoring, graphing), given equations of quadratic relations, including those that arise from real-world applications (e.g., break-even point)

A.2.1: determine, through investigation using a variety of tools and strategies (e.g., graphing with technology; looking for patterns in tables of values), and describe the meaning of negative exponents and of zero as an exponent

Dividing Exponential Expressions

Exponents and Power Rules

Multiplying Exponential Expressions

A.2.4: graph simple exponential relations, using paper and pencil, given their equations [e.g., y = 2 to the x power, y = 10 to the x power, y = (½) to the x power]

Compound Interest

Exponential Functions

Introduction to Exponential Functions

Logarithmic Functions

A.3.2: describe some characteristics of exponential relations arising from real-world applications (e.g., bacterial growth, drug absorption) by using tables of values (e.g., to show a constant ratio, or multiplicative growth or decay) and graphs (e.g., to show, with technology, that there is no maximum or minimum value)

Introduction to Exponential Functions

B.1.2: determine, through investigation (e.g., using spreadsheets and graphs), and describe the relationship between compound interest and exponential growth

B.1.4: calculate the total interest earned on an investment or paid on a loan by determining the difference between the amount and the principal [e.g., using I = A – P (or I = FV – PV)]

B.1.6: determine, through investigation using technology (e.g., a TVM Solver on a graphing calculator or on a website), the effect on the future value of a compound interest investment or loan of changing the total length of time, the interest rate, or the compounding period

B.2.4: gather, interpret, and compare information about current credit card interest rates and regulations, and determine, through investigation using technology, the effects of delayed payments on a credit card balance

B.2.5: solve problems involving applications of the compound interest formula to determine the cost of making a purchase on credit

C.1.4: solve design problems that satisfy given constraints (e.g., design a rectangular berm that would contain all the oil that could leak from a cylindrical storage tank of a given height and radius), using physical models (e.g., built from popsicle sticks, cardboard, duct tape) or drawings (e.g., made using design or drawing software), and state any assumptions made

C.2.1: solve problems, including those that arise from real-world applications (e.g., surveying, navigation), by determining the measures of the sides and angles of right triangles using the primary trigonometric ratios

Sine, Cosine, and Tangent Ratios

D.1.3: explain the distinction between the terms population and sample, describe the characteristics of a good sample, and explain why sampling is necessary (e.g., time, cost, or physical constraints)

Polling: City

Polling: Neighborhood

Populations and Samples

D.1.6: identify and describe properties associated with common distributions of data (e.g., normal, bimodal, skewed)

Mean, Median, and Mode

Polling: City

Populations and Samples

Real-Time Histogram

Sight vs. Sound Reactions

D.1.7: calculate, using formulas and/or technology (e.g., dynamic statistical software, spreadsheet, graphing calculator), and interpret measures of central tendency (i.e., mean, median, mode) and measures of spread (i.e., range, standard deviation)

Box-and-Whisker Plots

Describing Data Using Statistics

Polling: City

Populations and Samples

Real-Time Histogram

Sight vs. Sound Reactions

Stem-and-Leaf Plots

D.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)

Box-and-Whisker Plots

Describing Data Using Statistics

Mean, Median, and Mode

Polling: City

Populations and Samples

Real-Time Histogram

Sight vs. Sound Reactions

Stem-and-Leaf Plots

D.1.9: compare two or more sets of one-variable data, using measures of central tendency and measures of spread

Box-and-Whisker Plots

Describing Data Using Statistics

Mean, Median, and Mode

Real-Time Histogram

D.1.10: solve problems by interpreting and analysing one-variable data collected from secondary sources

Describing Data Using Statistics

D.2.1: identify examples of the use of probability in the media and various ways in which probability is represented (e.g., as a fraction, as a percent, as a decimal in the range 0 to 1)

Probability Simulations

Theoretical and Experimental Probability

D.2.2: determine the theoretical probability of an event (i.e., the ratio of the number of favourable outcomes to the total number of possible outcomes, where all outcomes are equally likely), and represent the probability in a variety of ways (e.g., as a fraction, as a percent, as a decimal in the range 0 to 1)

Binomial Probabilities

Independent and Dependent Events

Probability Simulations

Theoretical and Experimental Probability

D.2.3: perform a probability experiment (e.g., tossing a coin several times), represent the results using a frequency distribution, and use the distribution to determine the experimental probability of an event

Binomial Probabilities

Polling: City

D.2.4: compare, through investigation, the theoretical probability of an event with the experimental probability, and explain why they might differ

Geometric Probability

Independent and Dependent Events

Probability Simulations

Theoretical and Experimental Probability

Correlation last revised: 9/24/2019

This correlation lists the recommended Gizmos for this province's curriculum standards. Click any Gizmo title below for more information.