Problem 1The following data is givenᏆ13459 1214У24567911By hand, use linear least squares regression to determine the coefficients m and b in the function y = mx + b thatbest fits the data.Problem 1 required submission:☐ Handwritten (or printed) answers

Answer:To solve the problem using linear least squares regression, we need to determine the…

Answered: Problem 1 The following data is given Ꮖ…

Elements Of Electromagnetics

7th Edition

ISBN:9780190698614

Author:Sadiku, Matthew N. O.

Publisher:Sadiku, Matthew N. O.

ChapterMA: Math Assessment

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Problem 1/MatlabGrader (20 points) (Core Course Outcome 4) Develop a Matlab function myFit Exam that finds the best fit of the function p(t) = a sin³ (t) +bsin² (t) + csin(t) +d (1) to a given set of data points (t., p.) 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: well…
As an industrial engineer, you intend to use linear trend (or linear regression) method to solve a forecasting problem. You have decided to use the equation of y = m(x) + c to establish the relationship between the sales (y) and the related month (x). It is known that 8 consecutive months data (Jan to Aug) were used and they resulted to the following parameter values of m = 320 and c = 1017. Using the regression technique, estimate the percentage of sales improvement from December this year to June next year.
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: ☐…
Q2: File Upload الزامي ABET äbäi 15 solve the question on a piece of [Q2] paper and upload it as ONE FILE here .{as an image or PDF only} Question 2 Use the least square regression to fit the data in the following table to the equation yfit = ae*. 1.5 2 y 1.6 3.7 7 13.5 24.6 1 2.5 (A) Determine the values of a and 3. (B) What is the standard error of this estimation? (C) Using the fit equation, what the value of y at r = 2.25? إضافة ملف
Develop a Matlab function myFitExam that finds the best fit of the function p(t) = a 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.
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Problem 2: Note: Make sure to show all steps and work done in order to get the full credit. A set of experimental data is given as: x 0.4 0.8 1.6 2.3 800 980 1945 3600 Use a straight line to fit the data. y = ao + a,x. Find its coefficients Find standard deviation for the linear regression.
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?
Solve problem 4 in the correlation and regression handout. Submit your spreadsheet file
Forest Fires and Acres Burned Numbers (in thousands) of forest fires over the year and the number (in hundred thousands) of acres burned for 6 recent years are shown. The regression line equation is y'=-18.779+0.761x. The standard error of the estimate is sest 9.55. Find the 80% interval when x=60. Round intermediate answers to three decimal places. Round your final answers to two decimal places as needed. Number of fires x 58 47 84 62 57 45 Number of acres burned y 19 26 51 15 30 15 Send data to Excel One can be 80% confident that the interval
The following table presents the highway gasoline mileage performance and engine displacement for Audi vehicles for model year 2005. a) (5 Pts.) Fit simple linear model. Test for significance of the regression using alpha=0.05. Find the p-value for this test. What conclusions you can reach? b) (5 Pts.) Test Ho: P₁= -0.05 versus H₁: ₁
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Problem 1 The following data is given Ꮖ 1 3 4 5 9 12 14 У 2 4 5 6 7 9 11 By hand, use linear least squares regression to determine the coefficients m and b in the function y = mx + b that best fits the data. Problem 1 required submission: ☐ Handwritten (or printed) answers