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Math
- Interpret and rewrite algebraic expressions and equations in equivalent forms.
- Write, solve and graph linear equations, functions and inequalities in one and two variables.
- Write, solve and graph quadratic equations, functions and inequalities in one and two variables.
- Write, solve and graph absolute value equations, functions and inequalities in one and two variables.
- Write, solve and graph exponential and logarithmic equations and functions in one and two variables.
- Solve and graph polynomial equations and functions in one and two variables.
- Solve and graph radical equations and functions in one and two variables.
- Solve and graph rational equations and functions in one and two variables.
- Write and solve a system of two- and three-variable equations and inequalities that describe quantities or relationships.
- Solve problems involving sequences and series.
- Build mathematical foundations for financial literacy.
- Develop an understanding of basic accounting and economic principles.
- Describe the advantages and disadvantages of short-term and long-term purchases.
- Describe the advantages and disadvantages of financial and investment plans, including insurances.
- Prove and apply geometric theorems to solve problems.
- Apply properties of transformations to describe congruence or similarity.
- Use coordinate geometry to solve problems or prove relationships.
- Use geometric measurement and dimensions to solve problems.
- Make formal geometric constructions with a variety of tools and methods.
- Use properties and theorems related to circles.
- Apply geometric and algebraic representations of conic sections.
- Summarize, represent and interpret categorical and numerical data with one and two variables.
- Solve problems involving univariate and bivariate numerical data.
- Solve problems involving categorical data.
- Use and interpret independence and probability.
- Determine methods of data collection and make inferences from collected data.
- Use probability distributions to solve problems.
- Apply recursive methods to solve problems.
- Apply optimization and techniques from Graph Theory to solve problems.
- Apply techniques from Election Theory and Fair Division Theory to solve problems.
- Develop an understanding of the fundamentals of propositional logic, arguments and methods of proof.
- Apply properties from Set Theory to solve problems.
Florida B.E.S.T. Math
High School: Data Analysis and Probability: Solve problems involving univariate and bivariate numerical data.
For two or more sets of numerical univariate data, calculate and compare the appropriate measures of center and measures of variability, accounting for possible effects of outliers. Interpret any notable features of the shape of the data distribution.
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Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages. Recognize that there are data sets for which such a procedure is not appropriate.
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Estimate population percentages from data that has been fit to the normal distribution.
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Fit a linear function to bivariate numerical data that suggests a linear association and interpret the slope and y-intercept of the model. Use the model to solve real-world problems in terms of the context of the data.
- Estimating equations of lines of best fit, and using them to make predictions
- Estimating slope of line of best fit
- Estimating the line of best fit exercise
- Estimating with linear regression (linear models)
- Eyeballing the line of best fit
- Fitting a line to data
- Interpreting slope and y-intercept for linear models
- Interpreting slope of regression line
- Interpreting y-intercept in regression model
- Line of best fit: smoking in 1945
Given a scatter plot that represents bivariate numerical data, assess the fit of a given linear function by plotting and analyzing residuals.
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Given a scatter plot with a line of fit and residuals, determine the strength and direction of the correlation. Interpret strength and direction within a real-world context.
Compute the correlation coefficient of a linear model using technology. Interpret the strength and direction of the correlation coefficient.
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Fit a quadratic function to bivariate numerical data that suggests a quadratic association and interpret any intercepts or the vertex of the model. Use the model to solve real-world problems in terms of the context of the data.
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Fit an exponential function to bivariate numerical data that suggests an exponential association. Use the model to solve real-world problems in terms of the context of the data.
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