4. (35 points) Use multiple linear regression to fit the following experimental data, 12 1 4...
Use multiple linear regression to fit x1 0 0 1 2 0 1 2 2 1 x2 0 2 2 4 4 6 6 2 1 y 14 21 11 12 23 23 14 6 11 Compute the coefficients, the standard error of the estimate, and the correlation coefficient.
please solve using matlab 4. Nonlinear Regression Fit the below data with the following curve-fit equation y bi (ebr + 2 1.0000 1.5431 3.7622 10.0677 27.3082 Define a function of the sum of squared residuals (fSSR) as a function of the regression coefficients, b's. Minimize the fSSR function and determine the regression coefficients. Guess what would be the built-in math function to generate the original data? Plot the function in the existing figure with a smooth dashed line, calculate the...
Q4.. [40 points] Consider the multiple linear regression model given by y - XB -+ s, where y and e are vectors of size 8 × 1, X ls a matrix of size 8 x 3 and Disa vector of sze 3 × 1. Also, the following information are available e = 22 y -2 and XTy 3 1. [10 points) Estimate the regression coefficients in the model given above? 2. [4 points] Estimate the variance of the error term...
4. A simple linear regression was fit for a dataset with 35 data points. The sample variance of the response was found to be 2.4 and 62 was found to be 1.3. What was the value of R2 for this data?
Question 2 (36 points): A multiple linear regression analysis is performed and the following MINITAB output is observed: Regression Analysis: Fuel cell power versus H2 pressure and He flow The Regression Equation is Fuel cell power (W) = 2705.235 1.0745*H3 pressure (psi) + 3.2319"Ha flow Coef T-Value Term Constant Ha pressure (psi) Ha flow (ates) SE Coef 334.44 9.09 2.18 MS F-Value Analysis of Variance Source DE Regression Error Total 27 99 3231.9 7751.78 Answer to the following questions based...
1. Linear Regression Given 4 data points: 5 2 7 wl 9 15 Use simple linear regression to estimate ßo and ß, for the best-fit line Û=B. + B1x Calculate these values: L ñ | Sxx Sxy ß I I Sketch the regression line and the data points below
1. Linear Regression Given 4 data points: 5 2 7 wl 9 15 Use simple linear regression to estimate ßo and ß, for the best-fit line Û=B. + B1x Calculate these values: L ñ | Sxx Sxy ß I I Sketch the regression line and the data points below
Simple Linear Regression Problem Simple Linear Regression Problem QUESTION 4 SUMMARY OUTPUT Regression Statistics Multiple R Squared Adjusted Rsq Standard Error Observations 0.90 0.80 0.79 82.06 19.00 ANOVA MS 467247.5 6733.3 df Regression Residual Total 467247.5 114466.2 581713.7 17 Intercept Age Coefficients St Error 756.26 10.27 30.41 1.23 t Stat 24.87 -8.33 This output was obtained from data on the age of houses (in years) and the associated amount paid in rates (S). Predict the rates paid (in dollars correct...
True or false?: 1) If X and Y are standardized, then fit a linear regression line of standardized Y on standardized X, correlation between X and Y equals the slope of regression line. 2) If one calculates r for a set of numbers and then adds a constant to each value of one of the variables, the correlation will change. 3) The easiest way to determine if a relationship is linear is to calculate the regression line. 4) If the...
True or false: 1) If X and Y are standardized, then fit a linear regression line of standardized Y on standardized X, correlation between X and Y equals the slope of regression line. 2) If one calculates r for a set of numbers and then adds a constant to each value of one of the variables, the correlation will change. 3) The easiest way to determine if a relationship is linear is to calculate the regression line. 4) If the...