What is the purpose of this Matlab function?a) Perform a non-linear regression based on a spline-functionb) Interpolate the data on an equidistant grid and perform a numerical integrationc) Solve an ordinary differential equation that is represented by data values on a non-equidistant gridd) Determine the similarity of the two input vectors; the higher the resulting number the better is the agreement You get the following Matlab code from a fellow student:function[result]=what_do_i_do(x_vec_in,y_vec_in)a=min(x_vec_in);b=max(x_vec_in);dim1=length(x_vec_in);dim2=length(y_vec_in);if (dim1==dim2)n=10*dim1;x=[a:1/n:b];y=interp1(x_vec_in,y_vec_in,x,'spline');result 1/n* (0.5*(y(1)+y(end))+sum(y(2:end-1)));elsesprintf('The input vectors are of different length!')result=NaN;endendWhen you call the function with two example input vectors the result will bewhat_do_i_do([0134],[0 19 16])ans =21.3338

The Matlab function provided performs the following operations:Checks if the input vectors…

You get the following Matlab code from a fellow student: function [result]=what_do_i_do(x_vec_in,y_vec_in) a=min(x_vec_in); b=max(x_vec_in); dim1=length(x_vec_in); dim2=length(y_vec_in); if (dim1==dim2) n=10*dim1; x=[a:1/n:b]; y=interp1(x_vec_in,y_vec_in,x,'spline'); result 1/n* (0.5*(y(1)+y(end))+sum(y(2:end-1))); else sprintf('The input vectors are of different length!') result=NaN; end end When you call the function with two example input vectors the result will be what_do_i_do([0134],[0 19 16]) ans = 21.3338

You get the following Matlab code from a fellow student: function [result]=what_do_i_do(x_vec_in,y_vec_in) a=min(x_vec_in); b=max(x_vec_in); dim1=length(x_vec_in); dim2=length(y_vec_in); if (dim1==dim2) n=10dim1; x=[a:1/n:b]; y=interp1(x_vec_in,y_vec_in,x,'spline'); result 1/n (0.5*(y(1)+y(end))+sum(y(2:end-1))); else sprintf('The input vectors are of different length!') result=NaN; end end When you call the function with two example input vectors the result will be what_do_i_do([0134],[0 19 16]) ans = 21.3338

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

In a comprehensive road test on new car models, one variable measured is the time it takes a car to accelerate from 0 to 60 miles per hour. To model acceleration time, a regression analysis is conducted on a random sample of 129 new cars. TIME60: y = Elapsed time (in seconds) from 0 mph to 60 mph MAX: x = Maximum speed attained (miles per hour) The simple linear model E(y) = Bo + B1x was fit to the data. Computer printouts for the analysis are given below: NWEIGHTED LEAST SQUARES LINEAR REGRESSION OF TIME60 PREDICTOR VARIABLES COEFFICIENT STD ERROR STUDENT'S T CONSTANT 187171 0.63708 29.38 0.0000 0.0000 MAX -0.08365 0.00491 -17.05 0.6960 0.6937 R-SQUARED RESID. MEAN SQUARE (MSE) 1.28695 ADJUSTED R-SQUARED STAND ARD DEVIATION 113444 SOURCE DF MS F REGRESSION 374.285 0.0000 374.285 1.28695 290.83 RESIDUAL 127 163.443 TOTAL 128 537.728 CASES INCLUDED 129 MISSING CASES 0 Fill in the blank: "At a =.05, there is between maximum speed and acceleration time." O sufficient evidence of a…
Consider the following table, which shows a data set relating the number of full days hikers spent on the Appalachian trail (a very long trail that attracts ambitious hikers), and the number of miles they hiked along the trail. x (full days of hiking) y (miles hiked) 9 1 64 8 5 14 10 19 2 13 46 12 139 16 800 112 73 249 136 310 32 205 787 210
Data on tuition and mid-career salary are collected from a number of universities and colleges. The result of the data collection is the linear regression model ŷ=0.93x + 167 where x = annual tuition and y = average mid-career salary of graduates, both in thousands of dollars. 1. Which quantity is the independent variable? O average mid-career salary of graduates annual tuition OF 2. According to this model, what is the average salary for a graduate of a college or university where the annual tuition is $30,000? $ 3. What is the slope of this regression model?
Ankit
The annual expenditure for cell phones varies by the age of an individual. The average annual expenditure E(a) (in $) for individuals of age a (in years) is given below:a: 20, 30, 40, 50, 60, 70E(a): 502, 658, 649, 627, 476, 2131. Use quadratic regression to find the model that best represents the data.2. At what age is the yearly expenditure for cell phones the greatest? Round the answer to the nearest year. YOU MUST SHOW THE WORK FOR THIS PART!
A local University conducted a survey of over 2,000 MBA alumni to explore the issue of work-life balance. Each participant received a score ranging from 0 to 100, with lower scores indicating a higher imbalance between work and life. A sample of the data is available below. Let x=average number of hours worked per week and y= work-life balance scale score for each MBA alumnus. Investigate the link between these two variables by conducting a complete simple linear regression analysis of the data. Summarize your findings. Hours WLB Score 50 74.09 45 72.45 50 52.93 55 44.33 50 69.15 60 54.79 55 56.26 60 20.44 55 6-.64 50 69.15 70 29.16 45 72.45 40 33.25 40 32.18 45 45.76 a. What is the test statistic for the hypotheses? t=______ b. What is the p-value for the test statistic? p-value=________ c. What is the value for the coeffiecent of determination r^2? r^2=________
In a laboratory experiment, data were gathered on the life span (y in months) of 33 rats, units of daily protein intake (x1), and whether or not agent x2 (a proposed life-extending agent) was added to the rats' diet (x2 = 0 if agent x2 was not added, and x2 = 1 if agent was added). From the results of the experiment, the following regression model was developed:ŷ = 36 + .8x1 − 1.7x2Also provided are SSR = 60 and SST = 180.The test statistic for testing the significance of the model is _____. a. 5.00 b. .50 c. .25 d. .33
Solve b
A seafood-sales manager collected data on the maximum daily temperature, T, and the daily revenue from salmon sales, R, using sales receipts for 30 days selected at random. Using the data, the manager conducted a regression analysis and found the least-squares regression line to be Rˆ=126+2.37T. A hypothesis test was conducted to investigate whether there is a linear relationship between maximum daily temperature and the daily revenue from salmon sales. The standard error for the slope of the regression line is SEb1=0.65. Assuming the conditions for inference have been met, which of the following is closest to the value of the test statistic for the hypothesis test? t=0.274 A t=0.65 B t=1.54 C t=3.65 D t=193.85 E
Can brand, battery life, and camera resolution affect a smartphone's price? Use α = .05 to perform a regression analysis for the Smartphones01BC dataset and answer the following questions. Solve this problem using MegaStat, and write your complete answers in the Response Box so I know that you can interpret the output. Attach your MegaStat file so I can see that you used the correct analysis method to solve this problem. Download: Smartphones01BC a. Perform the regression and write the complete regression equation. b. Based on your regression equation, which brand increases the price of a smartphone the most? Use the statistics from your output to explain your answer. c. Which predictors are significant, and which are not? Use the statistics from your output to explain your answer. d. Use your regression equation to predict the price of an LG smartphone with a 40-hour battery and 12-megapixel camera.
Compare the linear regression data for two students walking in front of a motion sensor: Bob’s walk d = 0.75t + 2 r = 0.70 Tracey’s walk d = 0.75t + 2 r = 0.95 a) How are the movements of these walkers similar? different? b) Sketch possible distance versus time graphs for Bob and Tracey.
assume the final regression equation from the stepwise regression analysis of the dependent variable cost (C) and the 10 potential independent variables is as follows: C = -5000 + 75 D + 0.4 S - 130 PT + 100 NE Given that the final model is valid, interpret the coefficient of NE: On average, a plant constructed in northeast region of USA costs _____ than a plant constructed in other regions, while keeping other variables constant A) 100 dollars more B) 100 millions of dollars more C) 100 millions of dollars less D) 100 dollars less