Q2. The following data refers to 5 different countries' GDP per capita (GDP), and Inflation(Inf).BCD.9.028.0CountryGDP per Capita(S Billions)Inf (%)22.00.61.11.265.0 45.52.37.0Estimate the lincar OLS regression line E (GIP) = c B Inf and finterpret the estimatedvalues for the parametersb)a)İnvestigate if the model you set up is right or not via the Coefficient of Determinationand F test at a= 0.01Compute and inierpret if there is any Auto-Correiation belween error terms by thec)Durbin Watson test and interpret the result.

Given information: The data represents the values of the variables GDP per capita ($ Billions) and…

Answered: E. The following data refers to 5…

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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G The following table shows the weights of some persons in kilograms and their heights in centimeters: X Weight (kg) 60 70 59 90 Height (cm) 165 170 144 189 Compute the slop B1 needed for the linear regression equation. Selected Answer: Correct Answer: [None Given] 1.15 + 5%
Listed below is the multiple regression equation for predicting Y by X₁ through Xs. Y is the number of sales per month. X₁ is the number of sales calls made X2 is the number of hours on the showroom floor X3 is the amount spent on radio ads X is the number of text messages sent Xs is the number of email messages sent Regression Statistics R Square 0.634 Standard Error 7.6796 Observations 45 Intercept X₁ X₂ X3 XA Xs Coefficients Standard Error 6.8163 0.1005 -0.3207 0.2084 0.1221 0.0943 77.1211 1.9439 -11.123 0.1144 11.34 1.23 What is the computed value of the F statistic you would use to test the significance of the entire model? Round your answer to two decimal places.
The following is the simple regression results based on the data from Madrigal Corporation: Dependent variable – Machine maintenance costs Independent variable – Machine hours Computed values Intercept P 3,500 Coefficient on independent variable P 3.50 Coefficient of correlation 0.856 R2 0.733 What percentage of the variation in maintenance costs is explained by the independent variable? (use two decimal places, e.g. 82.20%, 55.31% or 0.82, 0.55, these will be counted as correct answers)
5:32 PM Tue Mar 1 + 94% A webassign.net A statistical program is recommended. A sales manager collected the following data on x=- years of experience and y = annual sales ($1,000s). The estimated regression equation for these data is ý = 83 + 4x. Years of Experience Annual Sales ($1,000s) Salesperson 1 80 3. 97 4 102 4 4. 107 6 103 6. 8 116 7 10 119 8 10 123 11 127 10 13 136 (a) Compute the residuals. Years of Annual Sales Experience ($1,000s) Residuals 80 87 3. 97 95 4 102 99 4 107 99 6. 103 107 8 116 115 10 119 123 10 123 123 11 127 127 13 136 135 Construct a residual plot. 16 16 12 12 8- 8 4 4 -4 -4 -8- -8- -12 -12 -16 -16 2 4 6 8 10 12 14 2. 4 6 8 10 12 14 Years of Experience Years of Exmerience Residuals Residuals
Would you please assist in answering this question with working out?Thank you. Q. Using a sample of recent university graduates, you estimate a simple linear regression using initial annual salary as the dependent variable and the graduate's weighted average mark (WAM) as the explanatory variable. If the regression model has an estimated intercept of 2200 and an estimated slope coefficient of 550, what is the predicted starting salary of a student with a WAM of 82?
= 12.3 The Regression Equation X E Rounding Numbers Calculator X xyzHomework Assessment + → C A A https://www.xyzhomework.com 80% Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in 3- millions of dollars). Determine if there is a significant linear correlation between advertising cost and profit . Use a significance level of 0.01 and round all values to 4 decimal places. Advertising Cost Profit 3 21 4 22 18 6. 23 30 8 33 23 10 31 Ho: p = 0 Ha: p # 0 Find the Linear Correlation Coefficient r= Find the p-value p-value = The p-value is O Less than (or equal to) a O Greater than a The p-value leads to a decișion to Reject Ho O Accept Ho O Do Not Reject Ho signific voters p. The n The conclusion is There is a significant positive linear correlation between advertising expense and profit. O There is a significant negative linear correlation between advertising expense and profit. There ie n cianifiannt linaar corralation…
The following table shows both current and projected data on the number, in millions, of Facebook users in a certain country. t = years since 2012 F = number of Facebookusers (millions) 0 9.7 1 10.5 2 10.8 3 12.2 4 13.1 5 13.2 6 13.8 (a) Plot the data. (b) Find the equation of the regression line. (Round regression line parameters to two decimal places.) F(t) = Add the graph of the regression line to the plot from part (a). (c) Explain in practical terms the meaning of the slope of the regression line. (Round your answers to two decimal places). The slope of the regression line is million users per year. The slope means that, from 2012 on, the number of Facebook users in the country is expected to increase by million each year.
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Which of the following statements is the CORRECT expression in APA format of the SPSS simple linear regression results provided below? Model Summary Adjusted R Square R R Square 817 .668 627 a. Predictors: (Constant), Experience years (year) ANOVA Regression Residual Sum of Squares 92.844 46.118 138.962 df Std. Error of the Estimate 2.401 1 Total a. Dependent Variable: Income (10 million VND/month) b. Predictors: (Constant), Experience years (year) Mean Square 92.844 5.765 Coefficients Unstandardized Coefficients B Std. Error (Constant) -.651 Experience years (year) 7856642.174 37841636.85 a. Dependent Variable: Income (10 million VND/month) .162 Standardized Coefficients Beta -.817 F 16.105 -4.013 .208 Sig. 004 Sig. 004 .841 A regression analysis was conducted with Income as criterion variable and Experience in Years as the predictor. Experience in Years was NOT a significant predictor of Income, 3= -0.82, t(9)= -4.013, p>0.05, and accounted for 66.80% of the variance in Income…
Item9 eBook Item 9 The following regression output was obtained from a study of architectural firms. The dependent variable is the total amount of fees in millions of dollars. Predictor Coefficient SE Coefficient t p-value Constant 9.601 3.153 3.045 0.010 x1 0.221 0.110 2.009 0.000 x2 − 1.168 0.577 − 2.024 0.028 x3 − 0.106 0.073 − 1.452 0.114 x4 0.631 0.361 1.748 0.001 x5 − 0.043 0.029 − 1.483 0.112 Analysis of Variance Source DF SS MS F p-value Regression 5 1,844.31 368.9 9.37 0.000 Residual Error 56 2,205.62 39.39 Total 61 4,049.93 x1 is the number of architects employed by the company. x2 is the number of engineers employed by the company. x3 is the number of years involved with health care projects. x4 is the number of states in which the firm operates. x5 is the percent of the firm’s work that is health…

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E. The following data refers to 5 different countries' GDP per capita (GDP), and Inflation B 0.6 D A 22.0 untry P per Capita Billions) (%) 1.1 28.0 9.0 1.2 65.0 45.5 2.3 7.0 Estimate the lincar OLS regression line E (GhIP) = c B Inf and linterpret the estimated es for the parameters