Problem 3 RecitationThe following table gives the approximate population of the US for selected years from 1835 to 19901835 1861 1905 1944 199030yearpopulation (millions) 20100160 280mxAssume that the population growth can be modeled with an exponential function p = be where x is the year andp is the population in millions. By hand, write the equation in linear form and use linear least squares regression todetermine the constants b and m for which the function best fits the data. Use the function to estimate the populationin the year 1960.Problem 3 required submission:Handwritten (or printed) answers.

Step 1: Transform the exponential equation in linear form. We begin by rewriting the given…

Answered: Problem 3 Recitation The following…

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

See similar textbooks

Similar questions

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
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
See 2 images
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: ☐…
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.
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…
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
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?
Can you explain how to get the graphs and what the equations mean? I'm also confused for the fill in the blanks portion. Please and thank you!
For all the following problems, 5. a) b) You need to show at least 3 iterations calculated manually with all steps. You do not need to include the M.files for the bisection method (bisect.m) and for false position (falspos.m). You must, however, show the command lines for the given functions with their variables and other parameters. Fanning friction factor For fluid flow in pipes, friction is described by a dimensionless number, the Fanning friction factor f. The Fanning friction factor is dependent on a number of parameters related to the size of the pipe and the fluid, which can all be represented by another dimensionless quantity, the Reynolds number Re. A formula that predicts ƒ given Re is the von Karman equation: 4log₁0 (Re√) - 0.4 = Typical values for the Reynolds number for turbulent flow are 10,000 to 500,000 and for the Fanning friction factor are 0.001 to 0.01. (a) Develop a function that uses bisection to solve for fgiven a user-supplied value of Re between 500 and…
B8
I wanted to know how to create plots like these in MATLAB. I belive they were called herpolhode plots.

SEE MORE QUESTIONS

Recommended textbooks for you

Elements Of Electromagnetics

Mechanical Engineering

ISBN:

9780190698614

Author:

Sadiku, Matthew N. O.

Publisher:

Oxford University Press

Mechanics of Materials (10th Edition)

Mechanical Engineering

ISBN:

9780134319650

Author:

Russell C. Hibbeler

Publisher:

PEARSON

Thermodynamics: An Engineering Approach

Mechanical Engineering

ISBN:

9781259822674

Author:

Yunus A. Cengel Dr., Michael A. Boles

Publisher:

McGraw-Hill Education

Elements Of Electromagnetics

Mechanical Engineering

ISBN:

9780190698614

Author:

Sadiku, Matthew N. O.

Publisher:

Oxford University Press

Mechanics of Materials (10th Edition)

Mechanical Engineering

ISBN:

9780134319650

Author:

Russell C. Hibbeler

Publisher:

PEARSON

Thermodynamics: An Engineering Approach

Mechanical Engineering

ISBN:

9781259822674

Author:

Yunus A. Cengel Dr., Michael A. Boles

Publisher:

McGraw-Hill Education

Control Systems Engineering

Mechanical Engineering

ISBN:

9781118170519

Author:

Norman S. Nise

Publisher:

WILEY

Mechanics of Materials (MindTap Course List)

Mechanical Engineering

ISBN:

9781337093347

Author:

Barry J. Goodno, James M. Gere

Publisher:

Cengage Learning

Engineering Mechanics: Statics

Mechanical Engineering

ISBN:

9781118807330

Author:

James L. Meriam, L. G. Kraige, J. N. Bolton

Publisher:

WILEY

SEE MORE TEXTBOOKS