Math Problem Statement
The table below shows the profit, , in dollars, from selling items.
x 1 2 3 6 9 14 p 75.6 87.4 89.4 36.6 -104.4 -535.4
Using your calculator to do a quadratic regression, express the profit as a function of the number of items sold.
Solution
To find the quadratic function that models the profit as a function of the number of items sold , we need to perform a quadratic regression using the given data. A quadratic function is of the form:
The given data points are:
Steps for Quadratic Regression:
- Input the data into your calculator:
- Enter the values into one list (e.g., ) and the values into another list (e.g., ).
- Perform quadratic regression:
- On most graphing calculators (like the TI-84), you can access this by:
- Going to Stat -> Calc -> QuadReg.
- Select the lists where you've stored the and values, and run the regression.
- On most graphing calculators (like the TI-84), you can access this by:
- Retrieve the equation:
- The calculator will output values for , , and , giving you the quadratic equation.
Result (Based on the data provided):
Performing the regression, we get the following equation:
Thus, the profit as a function of the number of items sold is:
This equation models the relationship between the number of items sold and the profit.
Would you like me to break down any steps or provide more details?
Here are 5 questions to expand this topic:
- How can we use this function to predict profits for different values of ?
- What does the negative coefficient for indicate about the profit behavior as more items are sold?
- How can we find the maximum profit using this quadratic model?
- What is the significance of the constant term in this function?
- Can we use this function to find the number of items that result in zero profit?
Tip: You can find the maximum or minimum value of a quadratic function by using the vertex formula .
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Math Problem Analysis
Mathematical Concepts
Algebra
Quadratic Regression
Data Analysis
Formulas
Quadratic equation formula: p(x) = ax^2 + bx + c
Theorems
Quadratic Regression
Suitable Grade Level
Grades 9-12