Graphic Plots (Linear Regression and Curve fitting)1.The following data is given:256.8.91315y781011121415Use linear least-squares regression to determine the coefficients m and b in thefunction y = mx +b that best fits the data.Make a plot that shows the function and the data points.2. Find the straight line, quadratic and cubic equations that fit to the following dataX1.21.51.82.63.14.34.95.3y4.55.15.86.77.07.37.67.4X5.76.47.17.68.69.29.8y7.26.96.65.14.53.42.73.Find the least-squares parabola for the data shown in Table below.X.346y343424.The boiling temperature of water T, at various altitudes h is given in the fol-lowing table. Determine a linear equation in the form T mh+b that bestfits the data. Use the equation for calculating the boiling temperature at5,000 m. Make a plot of the points and the equation.h (m)60015002300300061007900T(°C)10098.895.192.29081.275.6

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Graphic Plots (Linear Regression and Curve fitting) 1. The following data is given: 2 5 6. 8. 9 13 15 y 7 10 11 12 14 15 Use linear least-squares regression to determine the coefficients m and b in the function y Make a plot that shows the function and the data points. = mx +b that best fits the data.

Graphic Plots (Linear Regression and Curve fitting) 1. The following data is given: 2 5 6. 8. 9 13 15 y 7 10 11 12 14 15 Use linear least-squares regression to determine the coefficients m and b in the function y Make a plot that shows the function and the data points. = mx +b that best fits the data.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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# The table contains the state population and the number of licensed drivers in the state (both in millions) for the states with population under 1 million in 2014. The regression model for this data is y 0.7x where x is the state population (in millions) and y is the number of State licensed drivers (in millions) in the state. (A) Draw a scatter plot of the data and a graph of the model on the same axes. Choose the correct graph below OC Diverse) 07 Se pun CHANG The estimated population of state Jin 2014 is (Type a whole number Round to the nearest thousand as needed) 0.5 (8) If the population of state H in 2014 was about 1.6 million, use the model to estimate the number of licensed drivers in state H in 2014 The estimated number of licensed drivers in state H in 2014 is (Type a whole number. Round to the nearest thousand as needed) (C) If the number of licensed drivers in state J in 2014 was about 1,043.000, use the model to estimate the population of state Jin 2014 AOCDEFO А С OD…
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An experiment is run. The mass of an object is recorded over time. Time (min) Mass (g) 32 40 36 32 37 32 39 30 50 27 Using your calculator, run a linear regression to determine the equation of the line of best fit. Round to two decimal places, use x for the variable.y=Using your equation, estimate the mass of the object at 41 minutes.grams=
Experiment (10): Graphic Plots (Linear Regression and Curve fitting) 1. The following data is given: 2 5 8 13 15 y 7 8 10 11 12 14 15 Use linear least-squares regression to determine the coefficients m and b in the function y = mx +b that best fits the data. Make a plot that shows the function and the data points. %3D 2. Find the straight line, quadratic and cubic equations that fit to the following data 1.2 1.5 1.8 2.6 3.1 4.3 4.9 5.3 y 4.5 5.1 5.8 6.7 7.0 7.3 7.6 7.4 5.7 6.4 7.1 7.6 8.6 9.2 9.8 y 7.2 6.9 6.6 5.1 4.5 3.4 2.7 3. Find the least-squares parabola for the data shown in Table below. 2 3 4 5 y 3 4 3 4 4. The boiling temperature of water T, at various altitudes h is given in the fol- lowing table. Determine a linear equation in the form T = mh +b that best fits the data. Use the equation for calculating the boiling temperature at 5,000 m. Make a plot of the points and the equation. h (m) 600 1500 2300 3000 6100 7900 T( C) 100 98.8 95.1 92.2 90 81.2 75.6 23
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