Problem 25
Question
Use the regression capabilities of a graphing utility or a spreadsheet to find linear and quadratic models for the data. State which model best fits the data. $$ (0,769),(1,677),(2,601),(3,543),(4,489),(5,411) $$
Step-by-Step Solution
Verified Answer
The best-fitting model is the one with the highest correlation coefficient value, which indicates the best goodness of fit. The specific model (either linear or quadratic) will depend on the computed values for the given data set.
1Step 1: Input Data
Enter the data points \((0,769),(1,677),(2,601),(3,543),(4,489),(5,411)\) into a graphing utility or a spreadsheet for analysis.
2Step 2: Linear Regression
Using the appropriate tool or function, generate a linear regression model for the entered data. This will produce a linear equation in the form \(y = mx + c\), where \(m\) is the slope and \(c\) is the y-intercept.
3Step 3: Quadratic Regression
Repeat the process, this time generating a quadratic regression model. The output will be a quadratic equation in the form \(y = ax^2 + bx + c\), where \(a\), \(b\), and \(c\) are constants.
4Step 4: Model Selection
Compare the models using the goodness of fit - often indicated by the correlation coefficient, \(r\) or \(R^2\). The model with the highest value (closer to 1) is the best-fitting model for the data.
Other exercises in this chapter
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