See both images 17.6 Use least-squares regression to fit a straight line to56789x1 2 3 4y1 1.5 2 34 5810 13(a) Along with the slope and intercept, compute the standard errorof the estimate and the correlation coefficient. Plot the data andthe straight line. Assess the fit.(b) Recompute (a), but use polynomial regression to fit a parabolato the data. Compare the results with those of (a). Note: For the first three problems below, you must find the regression fits bywriting your own MATLAB functions that calculate the requested values.(1) Problem 17.6. Use the following instructions:a. Determine coefficients for the linear fit, as well as the r² value.b. Show your MATLAB function and Command Window.c. Plot the data and the linear fit.

17.6a)Let us make use of the excel for the computation of all the given valuesThe commands for excel…

Answered: 17.6 Use least-squares regression to…

Elements Of Electromagnetics

7th Edition

ISBN:9780190698614

Author:Sadiku, Matthew N. O.

Publisher:Sadiku, Matthew N. O.

ChapterMA: Math Assessment

Section: Chapter Questions

Problem 1.1MA

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Problem 6.5
Problem 3 Recitation The following table gives the approximate population of the US for selected years from 1835 to 1990 1835 1861 1905 1944 1990 30 year population (millions) 20 100 160 280 mx Assume that the population growth can be modeled with an exponential function p = be where x is the year and p is the population in millions. By hand, write the equation in linear form and use linear least squares regression to determine the constants b and m for which the function best fits the data. Use the function to estimate the population in the year 1960. Problem 3 required submission: Handwritten (or printed) answers.
8. What are the main stages of the FEM? 9. Make a sketch of a linear triangular finite element. Point the nodes and write the approximating polynomial. 10. Describe with one sentence what the shape functions in FEM are. 11. Special case of which method is the method of Galerkin? 12. What are the three main parts of a FEM program? 13. How can be increased the accuracy of the derivatives for linear finite elements in FEM postprocessor? 14. Specify three methods for force computation in FEM postprocessor.
.During the General Enhanced Community Quarantine, we were mandated to stay and work from home. We do a lot of walking as we do a lot of household chores at home. Applying vector addition, identify five displacements inside your house then calculate your total displacement. Use component method in finding your resultant displacement. Show your complete solution.
In your biomechanical testing lab, you perform a series of compression tests to determine the relationship between apparent bone density (p, units of g/cm³) and ultimate stress (ơult, units of MPa). Using the set of experimental measurements below, write an m-file to fit a power relationship of the form O uli = Ap to the data. Use the log transform method to linearize the system and data, followed by linear regression. Plot the data points and the power relationship on a single plot. Be sure to label your axes and provide a legend. Provide a printout of your m-file and a printout of the command window showing your results. Write down the best fit equation and box it. 8.76 5.25 4.26 5.51 3.88 18.45 2.09 13.72 5.42 2.17 Oult (MPa) p (g/cm³) 0.598 | 0.459 0.319 | 0.235 0.141 0.754 0.177 0.553 0.394 0.246
1) Graph 1: plot t on the abscissa versus y on the ordinate and (artistically) draw a smooth line through the points. The line need not actually go through each data point. 2) Graph 2: plot t^2 on the abscissa versus y on the ordinate and then perform a linear regression. Remember to plot both the raw data points and the line of best fit (with the two points used to draw it); also show the regression equation and r value on the graph. 3) On graph (1), what does the slope of the line tell you about the velocity of the ball? Be thorough! 4) On graph 2: a) What does the slope of the line tell you about the acceleration of the ball? Be thorough! b) Calculate g from the freefall data and the % error (in comparison to 9.81 m/s^2) using the results from the linear regression calculation. c) What do the values of the y-intercept and correlation coefficient (r) tell you?
Please help, this for Matlab the image is the first question with following 2 and 3 they go together. 2. Solving the question by using bisection.m with the stopping criterion at 1%. Report the root and # of iterations. 3. by using newton-Raphson matlab script with the stopping criterion at 0.1%. Report the root and # of iterations.
This for Matlab Please modify the script bisect.m to report/create the iteration table.
Some US census population data is given in the following table. Year yeatr 1980 1990 2000 population(y) 227 249 281 Here population is given in millions. 1. Fit a second degree polynomial passing through these points. 2. Use it to predict population in year 2010 and 2020. Note: Develop the linear system of equations from the above theory and solve the system by LU Decomposition Method. (linear algebra)
Problem 1/MatlabGrader (20 points) (Core Course Outcome 4) Develop a Matlab function myFitExam that finds the best fit of the function p(t) = as sin³ (t) + b sin² (t) + csin(t) + d (1) to a given set of data points (ti, pi) using regression. Here t is in radians. The function input shall be ⚫t: column vector of data values t ⚫ p: column vector of data values p The function output shall be • a: scalar containing the best fit coefficient a b: scalar containing the best fit coefficient b c: scalar containing the best fit coefficient c d: scalar containing the best fit coefficient d In the function use only functions developed in this class in modules 1 - 4. You do not need to provide these functions in your submission. They will be provided when assessing your function after the deadline. Note: no assessments will be performed on your submitted function before the exam deadline. Scores on Canvas for this problem before the exam has been fully graded are meaningless. Required submission: ☐…

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