Construct a scatterplot and identify the mathematical model that best fits the data. Assume that the model is to be used only for the scope of the given data and consider only linear, quadratic, logarithmic, exponential, and power models. Use a calculator or computer to obtain the regression equation of the model that best fits the data. You may need to fit several models and compare the values of R². The table below shows the weight of crops of oranges and the resulting gallons of juice. Using the weight as the independent variable, find the regression equation of the best model. x (pounds of oranges). 4321 5012 5239 5366 8978 25413 y (gallons of orange juice) 341.3 391.5 399.6 417.2 656.1 1927.3 Oy=-13.07 +0.079x Oy=264.43 el.0001x Oy=-7511.9+923.99 In x Oy=0.079x0.998

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Construct a scatter plot and identify the mathematical model

E. Construct a scatterplot and identify the mathematical model that best fits the data.
Assume that the model is to be used only for the scope of the given data and consider only
linear, quadratic, logarithmic, exponential, and power models. Use a calculator or
computer to obtain the regression equation of the model that best fits the data. You may
need to fit several models and compare the values of R².
The table below shows the weight of crops of oranges and the resulting gallons of juice. Using
the weight as the independent variable, find the regression equation of the best model.
x (pounds of oranges). 4321 5012 5239 5366 8978 25413
y (gallons of orange juice) 341.3 391.5 399.6 417.2 656.1 1927.3
Oy=-13.07 +0.079x
Oy=264.43 e¹.000 1x
Oy=-7511.9+923.99 In x
Oy=0.079x0.998
Transcribed Image Text:E. Construct a scatterplot and identify the mathematical model that best fits the data. Assume that the model is to be used only for the scope of the given data and consider only linear, quadratic, logarithmic, exponential, and power models. Use a calculator or computer to obtain the regression equation of the model that best fits the data. You may need to fit several models and compare the values of R². The table below shows the weight of crops of oranges and the resulting gallons of juice. Using the weight as the independent variable, find the regression equation of the best model. x (pounds of oranges). 4321 5012 5239 5366 8978 25413 y (gallons of orange juice) 341.3 391.5 399.6 417.2 656.1 1927.3 Oy=-13.07 +0.079x Oy=264.43 e¹.000 1x Oy=-7511.9+923.99 In x Oy=0.079x0.998
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