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What does it mean when the second differences of the y-values in the data set are constant?
Model: Quadratic
Equation: y=0.2x^2
We will start by determining the type of function that best models the data. Then we will be able to write an exact equation that models the data.
We want to determine the most appropriate model for the given data set. Note that the x-values have a common difference of 1. Therefore, we can check if the y-values have a common difference, a common ratio, or constant second differences. It will tell us which model is most appropriate for the data set.
The y-values have: | The model is: |
---|---|
A common difference | Linear |
A common ratio | Exponential |
Constant second differences | Quadratic |
We can exclude the possibility of an exponential model, since the y-value in the second pair is 0. Let's check for a common difference!
x | y | First differences |
---|---|---|
- 1 | 0.2 | |
0 | 0 | -0.2 ↩ |
1 | 0.2 | +0.2 ↩ |
2 | 0.8 | +0.6 ↩ |
3 | 1.8 | +1 ↩ |
4 | 3.2 | +1.4 ↩ |
x | y | First differences | Second differences |
---|---|---|---|
- 1 | 0.2 | ||
0 | 0 | -0.2 ↩ | |
1 | 0.2 | +0.2 ↩ | +0.4 ↩ |
2 | 0.8 | +0.6 ↩ | +0.4 ↩ |
3 | 1.8 | +1 ↩ | +0.4 ↩ |
4 | 3.2 | +1.4 ↩ | +0.4 ↩ |
The second differences of the y-values are all 0.4, so a quadratic model fits the data.
x= - 1, y= 0.2
(- a)^2=a^2
a(- b)=- a * b
Rearrange equation
(I):Add (II)
(I):Add terms
(I):.LHS /2.=.RHS /2.
(II):a= 0.2
(II):LHS-0.2=RHS-0.2