The relationship between a company's sales revenues and R&D research is given in the table below. Years 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Y 22 26 27 30 37 40 43 50 55 60 3 5 6 6 7 8 9 10 024 12 14 Y: Sales Revenues (Million TL) X: R&D Expenditures (Million TL) Since there is a relationship between two variables Y - Bo + B₁X; +V; the regression equation: a) Estimate its parameters (coefficients). b) Calculate the estimated values, error terms (residual values) and the sum of squares of the residuals, c) Calculate the variance of the error terms, the variance of the parameter estimators and the standard error values, d) Find the covariance value of the parameter estimators, e) Find the coefficient of determination and the corrected coefficient of determination, f) (a -0.05) Estimate the range for the parameters at the significance level, g) Conduct t and F tests for the model, (with 95% confidence probability) h) Calculate the correlation coefficient, 1) Prepare an analysis of variance (ANOVA) table for the regression model. Note: Use all formulas on the formula sheet.
The relationship between a company's sales revenues and R&D research is given in the table below. Years 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Y 22 26 27 30 37 40 43 50 55 60 3 5 6 6 7 8 9 10 024 12 14 Y: Sales Revenues (Million TL) X: R&D Expenditures (Million TL) Since there is a relationship between two variables Y - Bo + B₁X; +V; the regression equation: a) Estimate its parameters (coefficients). b) Calculate the estimated values, error terms (residual values) and the sum of squares of the residuals, c) Calculate the variance of the error terms, the variance of the parameter estimators and the standard error values, d) Find the covariance value of the parameter estimators, e) Find the coefficient of determination and the corrected coefficient of determination, f) (a -0.05) Estimate the range for the parameters at the significance level, g) Conduct t and F tests for the model, (with 95% confidence probability) h) Calculate the correlation coefficient, 1) Prepare an analysis of variance (ANOVA) table for the regression model. Note: Use all formulas on the formula sheet.
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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Transcribed Image Text:The relationship between a company's sales revenues and R&D research is given in
the table below.
Years
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Y
22
26
27
30
37
40
43
50
55
60
X
3
in
5
6
6
7
8
9
10
12
24
14
Y: Sales Revenues (Million TL)
X: R&D Expenditures (Million TL)
Since there is a relationship between two variables - Bo + B,X, +U; the regression
equation;
a) Estimate its parameters (coefficients).
b) Calculate the estimated values, error terms (residual values) and the sum of squares of
the residuals,
c) Calculate the variance of the error terms, the variance of the parameter estimators and
the standard error values,
d) Find the covariance value of the parameter estimators,
e) Find the coefficient of determination and the corrected coefficient of determination,
f) (a -0.05 ) Estimate the range for the parameters at the significance level,
g) Conduct t and F tests for the model, (with 95% confidence probability)
h) Calculate the correlation coefficient,
1) Prepare an analysis of variance (ANOVA) table for the regression model.
Note: Use all formulas on the formula sheet.
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Step 1: State the given information.
VIEWStep 2: Estimates the parameter of regression equation.
VIEWStep 3: Calculate estimated value, error term(residual) and sum of square of residual.
VIEWStep 4: Calculate the variance of error term and variance of estimated parameters and its standard error.
VIEWStep 5: Determine the covariance value of parameters and value of determination coefficient.
VIEWStep 6: Estimate the range of parameters at level of significance alpha=0.05
VIEWStep 7: Conduct the t and F test for model at confidence level 0.95.
VIEWStep 8: Calculate the correlation coefficient and prepare the anova table
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