Q3. Use Lagrange interpolating polynomials of orderа) 1b) 2c) 3to determine y at x=1.32 for the data given below.1.250.2231Xị1.201.301.351.401.451.50yi0.18230.26240.30010.33650.37160.4055

Let x0=1.20x1=1.25x2=1.30x3=1.35fx0=0.1823fx1=0.2231fx2=0.2624fx3=0.3001 The, Lagrange…

Q3. Use Lagrange interpolating polynomials of order а) 1 b) 2 c) 3 to determine y at x=1.32 for the data given below. 1.20 1.25 1.30 0.2624 Xi 1.35 1.40 1.45 1.50 yi 0.1823 0.2231 0.3001 0.3365 0.3716 0.4055

Q3. Use Lagrange interpolating polynomials of order а) 1 b) 2 c) 3 to determine y at x=1.32 for the data given below. 1.20 1.25 1.30 0.2624 Xi 1.35 1.40 1.45 1.50 yi 0.1823 0.2231 0.3001 0.3365 0.3716 0.4055

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

See similar textbooks

Similar questions

I would only need help with e and f
The point (9.1,71) is a point on the scatterplot. Draw the graph of the regression line on the scatterplot on the back of this paper using the y-intercept and the point(I = 3,y = 191). Indicate the residual for z = 9.1 by drawing the vertical line between(9.1, 71) and the corresponding point on the regression line. Will the residual be a positive or negative value?(f) Find the value of the residual for x = 9.1.
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.307 b=32.392 r²=0.675684 r=-0.822 Use this to predict the number of situps a person who watches 12.5 hours of TV can do (to one decimal place)
Find the integral monthly average price of each item (sugar, Flour, Eggs, Cooking Oil) given in the table. Then draw the Bar- Graph, Pictogram and Pie Chart of the obtained data (Items Vs monthly average prices).
You performed a regression analysis of a set of bibariate data (two variables) and found that the coefficient od determination was .99 for a quadratic model and .88 for cubic model Explain which model you would use and why
Obtain the descriptive statistics for each type of fertilizer. Interpret the result
Find the z-score corresponding to a score of X=50. u=60 and o=5 u=45 and o=5 u=40 and o=5 u=37 and o=5 u=59 and o=5
Employ Lagrange's interpolation method to find the value of f(x) using the following set of values when a = 1.7. Given that Lo(1.7) = 0.79, L1(1.7) = -0.63 and L2(1.7) = 0.54. 1.1 2.2 3.2 f(x) 3 4 7 3.63 O 3.74 1.11 8.67
Create a quadratic model for the data shown in the table 1 -1 X -1 -1 y Oy=0.85r² +0.11 - 1.78 y = 0.98x² -0.74 - 0.82 y = 0.112²1.78x +.9998 X y = -0.85x² -0.11x +1.78 2 2 5 20
Determine the z-value of x=25 if 4 = 16 and o = 3.
The first divided difference f[xo, x1] for the following data is xo = 1, x1 = 10, f[æo] = 7, f[x1] = 23
The table lists the average monthly cost to workers for family health insurance for various years. Year, x Average Monthly Cost to Workers for Family Health Insurance $298 a) Use a graphing calculator to fit a regression line to the data. b) Predict the average monthly cost to workers for family health insurance in 2020, and compare the value with $493.3, which is obtained using the points (1,340) and (4,386). c) Find the correlation coefficient for the regression line, and determine whether the line fits the data closely. 2009, 0 2010, 1 2011, 2 340 348 2012, 3 367 2013, 4 2014, 5 386 406 a) The linear equation of the regression line that best models the data is y =x+. (Round to the nearest hundredth as needed.) b) The average monthly cost to workers for family health insurance in 2020 is predicted to be $ (Round to the nearest cent as needed.) Compare the above obtained value with $493.3 This value is $ $493.3 c) The correlation coefficient is (Round to the nearest thousandth as…