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What does it mean when the second differences of the y-values in the data set are almost equal?
Model: Quadratic
Equation: y=3x^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 |
Sometimes data does not fall exactly into the models listed above. In that case, we have to round our results and see when they are the closest to being constant. Let's take a look at our table.
x | y |
---|---|
0 | 0 |
1 | 3 |
2 | 11.3 |
3 | 24.7 |
4 | 43.3 |
x | y | First differences |
---|---|---|
0 | 0 | |
1 | 3 | +3 ↩ |
2 | 11.3 | +8.3 ↩ |
3 | 24.7 | +13.4 ↩ |
4 | 43.3 | +18.6 ↩ |
As we can see, the differences between the consecutive y-values are far from being constant. Therefore we have to check the second differences.
x | y | First differences | Second differences |
---|---|---|---|
0 | 0 | ||
1 | 3 | +3 ↩ | |
2 | 11.3 | +8.3 ↩ | +5.3 ↩ |
3 | 24.7 | +13.4 ↩ | +5.1 ↩ |
4 | 43.3 | +18.6 ↩ | +5.2 ↩ |
The second differences of the y-values are all approximately 5, so a quadratic model fits the data.
(I):LHS-a=RHS-a
(II):b= 3-a
(II):Distribute 2
(II):Subtract term
(II):LHS-6=RHS-6
(II):.LHS /2.=.RHS /2.
(II):Round to nearest integer
(I):a ≈ 3
(I):Subtract term