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Henrico County Public Schools, Virginia
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 Algebra and Functions Data Analysis SOL Review Materials Frequently Asked Questions
The student will collect data and generate an equation for the curve (linear, quadratic, exponential, and logarithmic) of best fit to model real-world problems or applications. Students will use the best fit equation to interpolate function values, make decisions, and justify conclusions with algebraic and/or graphical models.
 Essential Knowledge and Skills Write an equation for the line of best fit, given a set of data points in a table, on a graph, or from a practical situation. Make predictions about unknown outcomes, using the equation of a line of best fit. Collect and analyze data to make decisions and justify conclusions. Investigate scatterplots to determine if patterns exist, and identify the patterns. Find an equation for the curve of best fit for data, using a graphing calculator. Models will include linear, quadratic, exponential, and logarithmic functions. Make predictions, using data, scatterplots, or equation of curve of best fit. Given a set of data, determine the model that would best describe the data. Describe the errors inherent in extrapolation beyond the range of the data. Estimate the correlation coefficient when given data and/or scatterplots. Essential Understandings The regression equation modeling a set of data points can be used to make predictions where appropriate. Data and scatterplots may indicate patterns that can be modeled with a function. Graphing calculators can be used to collect, organize, picture, and create an algebraic model of the data. Data that fit linear, quadratic, exponential, and logarithmic models arise from practical situations. Two variables may be strongly associated without a cause-and-effect relationship existing between them. Each data point may be considered to be comprised of two parts: fit (the part explained by the model) and residual (the result of chance variation or of variables not measured). Residual = Actual – Fitted Least squares regression generates the equation of the line that minimizes the sum of the squared distances between the data points and the line. A correlation coefficient measures the degree of association between two variables that are related linearly.
Vertical Articulation
1. SOL 8.13 - a) make comparisons/predictions/inferences, using information displayed in graphs; b) construct/analyze
scatterplots
2. SOL A.11 - collect/analyze data/determine equation of curve best fit to make predictions/solve real‐world problems, using models (linear/quad)
3. SOL AII.9 - collect/analyze data/determine equation of the curve of best fit/make predictions/solve real‐world problems, using models (poly/exp/log)
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