7. Find slop of a linear regression model for the following data:x = [1,2,3,4,5,6,7]z = [ 1.40, 3.78, 4.41, 4.60, 8.40, 8.64, 12.81].-1.7-0.50.5O 1.7CS Scanned with CamScannel

Introduction The regression model shows a relationship b/w and independent variable and a dependent…

Answered: 7. Find slop of a linear regression…

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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Interpret the following graphs for multiple linear regression and comment on the validity of model assumptions
Use multiple linear regression fit of the form y = a + bx₁ + cx₂ for the following data: 1.5 3 3 -1 X₁0 01 2 1 X₂ 0 1 0 1 2 1 2 3 -1 -2 -1.5 -12 -15 17 y 1644
- 16. Find the least squares regression line for the points (0, 8), (4, 5), (5, 3), (8,-1), and (10,-2). Round numerical values in your answer to two decimal places. a. y=-1.07x+2.63 b. y=-1.27x+8.36 c. y=-1.07x+8.36 d.y=-1.07x+10.54 c. y=-1.27x+2.63
The table contains data on vehicle speed (h) and fuel consumption (lt / 100km) of 5 randomly selected vehicles. Estimate the average fuel consumption of a vehicle traveling at 45 km / h using the simple linear regression equation between vehicle speed and fuel consumption. Speed 55 60 65 70 75 Consumption 13 12 11 10 9 a. 15 b. 8 c. 7 d. 20
3. A study of beer consumption using the annual data from 1980 -2001 produced the following regression: Y = 0.41 +0.052.X₁; −0.047X2; +0.032X3; −0.018X4i (0.027) (0.011) (0.009) (0.008) (0.009) R² = 0.94 F = 66.58 DW statistic=1.32, figures in the brackets are standard errors Where: Y₁ = Annual aggregate beer consumption in year t (billion pints) X₁₁ = Real disposable income income in year t ($ billions at 2001 prices) X2i = Price of beer in year t (index number with 2001 = 100) X31 Price of wine and sprits in year t (index number with 2001 = 100) = X4₁ = Price of cigarettes in year t (index number 2001 = 100) (a) What is the effect of a change in the price of beer on beer consumption? Does it have the correct sign? Explain. (b) Comment on the signs of the other three coefficients. Are they as expected? (c) Tests the significance of the coefficients on each of the variables Xit i = 1, 2, 3, 4. What assumptions have you made in carrying out these tests? (d) What conclusion do you draw…
1) Draw the graph of the estimated regression below. Y₁ = Bo + B₁X₁B₂X² + B3X²
The table shows data on the number of visitors to the UK in a month, (1000s), and the amount of money they spent, (£ millions), for each of 8 months. The correlation coefficient between and is 0.962 Give a reason to support fitting a regression model of the form to these data. Summary statistics are: For a regression model of the form . Find the value of b (the slope) correct to two decimal places. Now calculate a (the intercept) to calculate the regression model. Interpreting the value of b, each additional visitor spends £ __________ Using the equation calculated in part c, estimate the amount of money spent when the number of visitors to the UK in a month is 2,500,000
Q.1/ Use linear regression to fit the following experimental data. 图 2 3 4 5 7 10 y 5.2 7.8 10.7 13 19.3 26.5
3. Suppose that the following import function for Turkey is estimated for Turkey between 1980-2015. Import, a, + a,GDP; + ażER¸ + ut In order to measure the impact of 2001 crisis the regression is estimated based on the whole and two subsamples and the following RSS are obtained. Time period: 1980-2000 , RSS1= 69 Time period: 2001-2015, RSS2 =35 Time period: 1980-2015 , RSS = 160 Carry out the Chow test whether the regressions for the two periods are different at 5% significance level. (35 P)
The following table gives the data for the average temperature and the snow accumulation in several small towns for a single month. Determine the equation of the regression line, ŷ = bo + b₁x. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.05 level of significance. Critical Values of the Pearson Correlation Coefficient Average Temperature (°F) Average Temperatures and Snow Accumulations 42 31 24 45 38 18 33 21 25 9 12 27 7 15 22 30 13 20 37 Snow Accumulation (in.) 8
The following data on x maternal age in years of the young birth mothers and y = weight of baby born in grams summarizes the result of a study. Assume that a simple linear regression model y = Bo + B1x + e is an appropriate model for the study. x-bar = 17 (avg of x's) y-bar = 3004.1 (avg of y's) SSx = 20 SSxy %3D 4903 SSw 1539182.9 n 10 Calculate the value of s-(standard error of regression) and enter the answer to the nearest tenth (1 decimal place).
4. Consider a multiple linear regression model with two independent variables with 12 values in each variable. The coefficient of determination is obtained as 0.58. Evaluate the adjusted coefficient of detemination. for f nding Tote1 Cam ltinle lincor

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7. Find slop of a linear regression model for the following data: x = [1, 2₁ 3, 4, 5, 6, 7] z = [ 1.40, 3.78, 4.41, 4.60, 8.40, 8.64, 12.81]. -1.7 O -0.5 0 0.5 1.7