Presentation is loading. Please wait.

Presentation is loading. Please wait.

Curve Fitting with Polynomial Models Essential Questions

Similar presentations


Presentation on theme: "Curve Fitting with Polynomial Models Essential Questions"— Presentation transcript:

1 Curve Fitting with Polynomial Models Essential Questions How do we use finite differences to determine the degree of a polynomial that will fit a given set of data? How do we use technology to find polynomial models for a given set of data? Holt McDougal Algebra 2 Holt Algebra 2

2 Using Finite Differences to Determine Degree
Use finite differences to determine the degree of the polynomial that best describes the data. The x-values increase by a constant 2. Find the differences of the y-values. x 8 10 12 14 16 18 y 7.2 1.2 –8.3 –19.1 –29 –35.8 1. First differences: – 6 –9.5 –10.8 –9.9 –6.8 Not constant Second differences: –3.5 –1.3 0.9 3.1 Not constant Third differences: 2.2 2.2 2.2 Constant The third differences are constant A cubic polynomial best describes the data.

3 Often, real-world data can be too irregular for you to use finite differences or find a polynomial function that fits perfectly. In these situations, you can use the regression feature of your graphing calculator. Remember that the closer the R2-value is to 1, the better the function fits the data.

4 Curve Fitting Polynomial Models
The table below shows the opening value of a stock index on the first day of trading in various years. Use a polynomial model to estimate the value on the first day of trading in 2000. Year 1994 1995 1996 1997 1998 1999 Price ($) 683 652 948 1306 863 901 Step 1 Choose the degree of the polynomial model. Let x represent the number of years since Make a scatter plot of the data. The function appears to be cubic or quartic. Use the regression feature to check the R2-values. cubic: R2 ≈ quartic: R2 ≈ The quartic function is more appropriate choice.

5 Curve Fitting Polynomial Models
The table below shows the opening value of a stock index on the first day of trading in various years. Use a polynomial model to estimate the value on the first day of trading in 2000. Year 1994 1995 1996 1997 1998 1999 Price ($) 683 652 948 1306 863 901 Step 2 Write the polynomial model. f(x) = 32.23x4 – x x2 – x Step 3 Estimate the value at 2000. 2000 is 6 years after Substitute 6 for x in the quartic model. f(6) = 32.23(6)4 – (6) (6)2 – (6) Based on the model, the opening value was about $ in 2000.

6 Curve Fitting Polynomial Models
The table below shows the opening value of a stock index on the first day of trading in various years. Use a polynomial model to estimate the value on the first day of trading in 1999. Year 1994 1995 1996 2000 2003 2004 Price ($) 3754 3835 5117 11,497 8342 10,454 Step 1 Choose the degree of the polynomial model. Let x represent the number of years since Make a scatter plot of the data. The function appears to be cubic or quartic. Use the regression feature to check the R2-values. cubic: R2 ≈ quartic: R2 ≈ The quartic function is more appropriate choice.

7 Curve Fitting Polynomial Models
The table below shows the opening value of a stock index on the first day of trading in various years. Use a polynomial model to estimate the value on the first day of trading in 1999. Year 1994 1995 1996 2000 2003 2004 Price ($) 3754 3835 5117 11,497 8342 10,454 Step 1 Write the polynomial model. f(x) = 19.09x4 – x x2 – x Step 3 Estimate the value at 1999. 1999 is 5 years after Substitute 5 for x in the quartic model. f (5) = 19.09(5)4 – (5) (5)2 – (5) Based on the model, the opening value was about $ 11, in 1999.

8 Curve Fitting Polynomial Models
The table below shows the opening value of a stock index on the first day of trading in various years. Use a polynomial model to estimate the value on the first day of trading in 2002. Year 1994 1996 1998 2000 2001 2004 Price ($) 2814 3603 5429 3962 4117 3840 Step 1 Choose the degree of the polynomial model. Let x represent the number of years since Make a scatter plot of the data. The function appears to be cubic or quartic. Use the regression feature to check the R2-values. cubic: R2 ≈ quartic: R2 ≈ The quartic function is more appropriate choice.

9 Curve Fitting Polynomial Models
The table below shows the opening value of a stock index on the first day of trading in various years. Use a polynomial model to estimate the value on the first day of trading in 2002. Year 1994 1996 1998 2000 2001 2004 Price ($) 2814 3603 5429 3962 4117 3840 Step 1 Write the polynomial model. f(x) = 7.08x4 – x x2 – x Step 3 Estimate the value at 2002. 2002 is 8 years after Substitute 8 for x in the quartic model. f (8) = 7.08(8)4 – (8) (8)2 – (8) Based on the model, the opening value was about $ in 2002.

10 Lesson 15.1 Practice B


Download ppt "Curve Fitting with Polynomial Models Essential Questions"

Similar presentations


Ads by Google