Solve Quadratic Equations
By Graphing
Grab a warm-up off the wooden desk and get started!
Goals:
Warm-up #1
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Simplify. Give exact answers.
Warm-up #2
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Find each product.
Simplify. Answer should be exact.
Forms of Quadratic Functions
x-intercepts
y-intercept
vertex
open up/down
Key characteristics:
Forms of Quadratic Functions
Standard Form | Vertex Form | Factored Form |
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Match the following quadratic functions to their graphs. What strategies did you use?
A.
B.
C.
Solving Quadratics by graphing
To solve a quadratic by graphing the function must be in standard form set equal to zero. There can be at most 2 solutions to any quadratic function.
Log on to desmos!
Log on to desmos!
Finding the vertex is helpful!
How to find the vertex from…
Standard Form | Vertex Form | Factored Form |
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Solve by Graphing
Solve by Graphing
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Solve by Graphing
Solve by Graphing
Reflection Questions
Solve by Graphing
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Solve by Graphing
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Today’s google form!
Don’t forget to complete the google form to receive your participation/attendance credit for today. :-)
https://forms.gle/hqET1CbuuuppFi2m7
What do you
see
notice
wonder?
How do we solve functions (or system of functions) graphically?
Toss the Squish!
Today I learned... relating to exponential functions.
One question I still have is...
I know that I need to work more on...
Independent Practice: Delta Math
Resources
Mod 7 Standards
�Critical Area of Focus #3: Descriptive Statistics
In middle school, students developed an understanding of statistical problem solving through the format of the GAISE Model. They were expected to display numerical data and summarize it using measures of center and variability. By the end of middle school, students were creating scatter plots and recognizing linear trends in data. Now, they apply those concepts by using the GAISE model in the context of real-world applications. Students develop formal means of assessing how a model fits data. They use regression techniques to describe approximately linear relationships between quantities. Students use graphical representations and knowledge of the context to make judgements about the appropriateness of linear models. In Algebra 2. Mathematics 3, students will look at residuals to analyze the goodness of fit.
Statistics and Probability Overview
Interpreting Categorical and Quantitative Data
The GAISE Model (ODE Model Curriculum)
Guidelines for Assessment and Instruction in Statistics Education Report
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Mod 8 Standards
�S.ID.1 Represent data with plots on the real number line (dot plots, histograms, and box plots) in the context of real-world applications using the GAISE model.
S.ID.2 In the context of real-world applications by using the GAISE model, use statistics appropriate to the shape of the data distribution to compare center (median and mean) and spread (mean absolute deviation, interquartile range, and standard deviation) of two or more different data sets.
S.ID.3 In the context of real-world applications by using the GAISE model, interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).
S.ID.5 Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data.
S.ID.6 Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.�c. Fit a linear function for a scatterplot that suggests a linear association.
S.ID.7 Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.
S.ID.8 Compute (using technology) and interpret the correlation coefficient of a linear fit.
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