please answer a) and b) but ignore the matlab part in b)
please answer a) and b) but ignore the matlab part in b) 1. The following data...
The following data represent the bacterial growth in a liquid culture over a number of days: Day 0 4 8 12 16 20 Amount ×106 67.38 74.67 82.74 91.69 101.60 112.58 Determine the best equation to predict the amount of bacteria after 35 days using the parabolic model. (Round the final answer to two decimal places.) The amount of bacteria after 35 days is .
A wind tunnel test conducted on an airfoil section yielded the following data between the lift coefficient (CL) and the angle of attack (?): 12 1.40 16 1.71 20 1.38 de CL 0.11 0.55 0.95 You are required to develop a suitable polynomial relationship between ? and CL and fit a curve to the data points by the least-squares method using (a) hand calculations and (b) Matlab programming Hint: A quadratic equation (parabola) y(x)-aa,x +a x' can be used in...
only (c) please Find the least squares fit to the data x0 12 (a) By a linear function. Plot your linear function along with the data on a coordinate system. (b) By a quadratic polynomial. Sketch the graph. c) By a function of the form ya2 b2*. 2-1 Find the least squares fit to the data x0 12 (a) By a linear function. Plot your linear function along with the data on a coordinate system. (b) By a quadratic polynomial....
HELP!! In Matlab The scenario is simple: A set of (x,y) data is available in the form of a simple text file – the first column represents x-values and the second column represents y-values. The task at hand is to provide the best model (or curve fit) to this set of data. Your application should provide the means to fit the following curve types to the data: Linear (first order polynomial) of form (?? = ???? + ??) with non-zero...
MATLAB code please Obtain a temperature data of Reno from September 2016. Find the data for a typical sunny day, between 6am to 6pm. Write a MATLAB code that uses linear least squares to fit the data. Then, obtain the same temperature data from the same day in year 2017. Plot the data points and the regression line on the same graph. Does the least-squares line fit the data from 2017? Why or why not? Discuss your result.
USING MATLAB. For given data, estimate the length when time is at 3.5 seconds and at 13 seconds by utilizing the maximum number of data given, and provide the equation for the best fit curve, and plot the curve against the data. (a) Linear regression method (b) Exponential Function (c) Power Function (d) Saturation Function (e) Polynomial regression (f) Lagrange polynomial (8) Newton's divided-difference polynomial Time (sec) Length (in) 10 17 18 25 28 30 30 10 15 36 38
Suppose that the data (X1, Y), ... (Xn, Yn is generated by the following ("true") model: a+ bX; + сX; +ei, where a, b, c are some parameters and ei are independent errors with zero mean and variance a2. Suppose that we fit the simple linear regression model to the data (i.e. we ignore the quadratic term cX2) using the OLS method. Find the expectation of the residual from the fit. Suppose that the data (X1, Y), ... (Xn, Yn...
Please solve this using matlab and type in the codes here The following data was obtained when the stopping distance d of a car on a wet road was measured as a function of the speed v when the brakes were applied: v (mi/h) 12.5 25 37.5 50 62.5 75 d (ft) 20 59 118 197 299 420 Use polyfit function to determine the coefficients of a quadratic polynomial d = a_2 v^2 + a_1 v + a_0 that best...
help wanted?? thank you explain correctly Problem 1 Use the trapezoidal rule technique to approximate the following integrals: a) 「(x2+1)dr(Note: use 0.5 increments forx) b) sina d INote: use a MATLAB function to subdivide the interval into eight equal parts) c e dx (Note: use 0.25 increments for x Problem 2 Use the Simpson's rule to evaluate the following integrals aDdr Problem 3: Given the polynomial: x3-6x2 + 30-0, Use MATLAB to find all roots of this polynomial. Use MATLAB's...
Using MATLAB, The following data is given: 13 14 15 15 2 10 12 (a) Use linear least-squares regression to determine the coefficients m and b in the function y - mx+b that best fits the data (b) Make a plot that shows the function and the data points.