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We fit a GARCH (1, 1) model and display the MLE of the fitted model belovw > summary(dax.garch) C...
Using R output provided 1). Perform hypothesis testing for B(beta)1=2 using A(alpha)=0.05 > summary(ls) Call: Residuals:...
Using R output provided
1). Perform hypothesis testing for B(beta)1=2 using
A(alpha)=0.05
> summary(ls) Call: Residuals: Min 1Q Median 3Q Max 0.20283 -0.14691 -0.02255 0.06655 0.44541 Coefficients: (Intercept) 0.365100.099043.686 0.003586 ** Signif. codes: 0 '***' 0.001 '0.01 '*'0.05 '.' 0.1''1 Estimate Std. Error t value Pr>Itl) 0.96683 0.18292 5.286 0.000258** Residual standard error: 0.1932 on 11 degrees of freedom Multiple R-squared 0.7175, Adjusted R-squared: 0.6918 F-statistic: 27.94 on 1 and 11 DF, p-value: 0.0002581 anovaCLs) Analysis of Variance Table Response:...
2.-Interpret the following regression model Call: lm(formula = Sale.Price ~ Lot.Size + Square.Feet + Num.Baths + API.2011 + dis_coast + I(dis_fwy * dis_down * dis_coast) + Pool, data = Train...
2.-Interpret the following regression model Call: lm(formula = Sale.Price ~ Lot.Size + Square.Feet + Num.Baths + API.2011 + dis_coast + I(dis_fwy * dis_down * dis_coast) + Pool, data = Training) Residuals: Min 1Q Median 3Q Max -920838 -84637 -19943 68311 745239 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -7.375e+05 7.138e+04 -10.332 < 2e-16 *** Lot.Size -5.217e-01 1.139e-01 -4.581 5.34e-06 *** Square.Feet 1.124e+02 1.086e+01 10.349 < 2e-16 *** Num.Baths 3.063e+04 9.635e+03 3.179 0.00153 ** API.2011 1.246e+03 8.650e+01 14.405 < 2e-16...
Consider the following regression results: Describe how the response y depends on the regressor x. What...
Consider the following regression results:
Describe how the response y depends on the regressor x. What is
the formula for the regression line? What is the B0 and B1, and
what do these coefficients represent? The Residuals vs. fitted plot
is used to assess what assumption? What does the above plot tell
you about your data? (remember to round all answers to 3 decimal
places)
Call: Im(formula = y ~ X, data = d) Residuals: Min 1Q Median 3Q Max...
Therapy Study " A hospital administrator wishes to assess the relationship between a patient's level of anxiety (x) and that patient's level of satisfaction (y) with a new hospital treatm...
Therapy Study " A hospital administrator wishes to assess the relationship between a patient's level of anxiety (x) and that patient's level of satisfaction (y) with a new hospital treatment. A linear regression analysis was performed on data for a random sample of n -46 patients who went through this new therapy treatment. A summary of the results is given below: 3. StdDev Min. 1st Qu. Median 3rd Qu. Max. Mean Satisfaction 61.57 17.24 26.00 48.25 60.0076.75 92.00 Anxiety 2.287...
A client of yours wants to find out the best microbial environment for C. elegans. In...
A client of yours wants to find out the best microbial environment for C. elegans. In previous meetings, the client told you that C. elegans feed on bacteria but may also be killed by certain bacteria. Therefore, it is important to figure out what bacteria are beneficial to C. elegans. In particular, the client was interested in studying the association between the density of Gluconobacter and the density of C. elegans. The client had collected some pilot data for this...
please show your explanation thanks! ## ## Call: ## Im(formula = mpg ~ disp + hp...
please show your explanation thanks!
## ## Call: ## Im(formula = mpg ~ disp + hp + wt + osec, data = mtcars.train.df) ## ## Residuals: Min 1Q Median ## -4.3442 -1.1687 -0.4033 3Q Max 1.0519 5.9623 ## ## Coefficients: Estimate Std. Error t value Pr>t) ## (Intercept) 31.204891 10.909916 2.860 0.00967 ** ## disp 0.009432 0.012308 0.766 0.45245 ## hp -0.032908 0.025528 -1.289 0.21208 ## wt -4.978374 1.434757 -3.470 0.00242 ** ## qsec 0.434043 0.576267 0.753 0.46011 ## ---...
Q) The CO2 dataset in R has data on plants from Quebec and Mississippi (denoted by the variable name ‘Type’) that were subjected to two different treatments (denoted by the variable name “Treatment”)...
Q) The CO2 dataset in R has data on plants from Quebec
and Mississippi (denoted by the variable name ‘Type’) that were
subjected to two different treatments (denoted by the variable name
“Treatment”), chilled or nonchilled. I ran two regression models to
see what variables best describe CO2 uptake of plants, given
different conditions, with the output below:
What are the regression equations for models 1 and
2?
What kind of variable is “Treatment”?
What does the sign of the...
What is the dependent variable in this analysis? What are the independent variables in this analysis?...
What is the dependent variable in this analysis? What are the independent variables in this analysis? Draw a diagram representing the model being tested. What are the assumptions which need to be met PRIOR to interpreting the results of the analysis? What do you conclude about the quality of the model? What do you conclude about each of the predictors? Interpret the coefficient for any significant predictors. ## ## Call: ## lm(formula = Ought_Score ~ Inherence_Bias + Ought_Score + educ...
To investigate the impact of advertising medias (say youtube) on sales, we construct the fol- lowing...
To investigate the impact of advertising medias (say youtube) on sales, we construct the fol- lowing simple linear regression model Y; = Bo + B12; + &i with std N(0,0%) where Y is the sales and x is advertising budget in thousands of dollars. The summary table is given below: Formula: Call: 1m (formula = sales youtube, data = marketing) Residuals: Min 1Q Median 3Q Max -10.0632 -2.3454 -0.2295 2.4805 8.6548 F=MSR/MSE, R2 = SSR/SSTO ANOVA decomposition: SSTO = SSE...
UESTION 7 Fuel efficiency in auto-mobiles can be influences by a number of characteristics. See the...
UESTION 7 Fuel efficiency in auto-mobiles can be influences by a number of characteristics. See the linear regression output below and answer the following questions Results of linear regression analysis are shown below: Call: lm (formula = mpg ~ ., data = auto-mpg) Residuals: Min 1Q Median 3Q Max -8.6927-2.3864 -0.0801 2.0291 14.3607 Coefficients: Estimate Std. Error t value Pr>Itl) (Intercept) -1.454e+01 4.764e+00 -3.051 0.00244* cyl disp hp gvw accel year -3.299e-01 3.321e-01 -0.993 0.32122 7.678e-03 7.358e-03 1.044 0.29733 -3.914e-04...
Using R output provided
1). Perform hypothesis testing for B(beta)1=2 using
A(alpha)=0.05
> summary(ls) Call: Residuals: Min 1Q Median 3Q Max 0.20283 -0.14691 -0.02255 0.06655 0.44541 Coefficients: (Intercept) 0.365100.099043.686 0.003586 ** Signif. codes: 0 '***' 0.001 '0.01 '*'0.05 '.' 0.1''1 Estimate Std. Error t value Pr>Itl) 0.96683 0.18292 5.286 0.000258** Residual standard error: 0.1932 on 11 degrees of freedom Multiple R-squared 0.7175, Adjusted R-squared: 0.6918 F-statistic: 27.94 on 1 and 11 DF, p-value: 0.0002581 anovaCLs) Analysis of Variance Table Response:...
Consider the following regression results:
Describe how the response y depends on the regressor x. What is
the formula for the regression line? What is the B0 and B1, and
what do these coefficients represent? The Residuals vs. fitted plot
is used to assess what assumption? What does the above plot tell
you about your data? (remember to round all answers to 3 decimal
places)
Call: Im(formula = y ~ X, data = d) Residuals: Min 1Q Median 3Q Max...
Therapy Study " A hospital administrator wishes to assess the relationship between a patient's level of anxiety (x) and that patient's level of satisfaction (y) with a new hospital treatment. A linear regression analysis was performed on data for a random sample of n -46 patients who went through this new therapy treatment. A summary of the results is given below: 3. StdDev Min. 1st Qu. Median 3rd Qu. Max. Mean Satisfaction 61.57 17.24 26.00 48.25 60.0076.75 92.00 Anxiety 2.287...
A client of yours wants to find out the best microbial environment for C. elegans. In previous meetings, the client told you that C. elegans feed on bacteria but may also be killed by certain bacteria. Therefore, it is important to figure out what bacteria are beneficial to C. elegans. In particular, the client was interested in studying the association between the density of Gluconobacter and the density of C. elegans. The client had collected some pilot data for this...
please show your explanation thanks!
## ## Call: ## Im(formula = mpg ~ disp + hp + wt + osec, data = mtcars.train.df) ## ## Residuals: Min 1Q Median ## -4.3442 -1.1687 -0.4033 3Q Max 1.0519 5.9623 ## ## Coefficients: Estimate Std. Error t value Pr>t) ## (Intercept) 31.204891 10.909916 2.860 0.00967 ** ## disp 0.009432 0.012308 0.766 0.45245 ## hp -0.032908 0.025528 -1.289 0.21208 ## wt -4.978374 1.434757 -3.470 0.00242 ** ## qsec 0.434043 0.576267 0.753 0.46011 ## ---...
Q) The CO2 dataset in R has data on plants from Quebec
and Mississippi (denoted by the variable name ‘Type’) that were
subjected to two different treatments (denoted by the variable name
“Treatment”), chilled or nonchilled. I ran two regression models to
see what variables best describe CO2 uptake of plants, given
different conditions, with the output below:
What are the regression equations for models 1 and
2?
What kind of variable is “Treatment”?
What does the sign of the...
To investigate the impact of advertising medias (say youtube) on sales, we construct the fol- lowing simple linear regression model Y; = Bo + B12; + &i with std N(0,0%) where Y is the sales and x is advertising budget in thousands of dollars. The summary table is given below: Formula: Call: 1m (formula = sales youtube, data = marketing) Residuals: Min 1Q Median 3Q Max -10.0632 -2.3454 -0.2295 2.4805 8.6548 F=MSR/MSE, R2 = SSR/SSTO ANOVA decomposition: SSTO = SSE...
UESTION 7 Fuel efficiency in auto-mobiles can be influences by a number of characteristics. See the linear regression output below and answer the following questions Results of linear regression analysis are shown below: Call: lm (formula = mpg ~ ., data = auto-mpg) Residuals: Min 1Q Median 3Q Max -8.6927-2.3864 -0.0801 2.0291 14.3607 Coefficients: Estimate Std. Error t value Pr>Itl) (Intercept) -1.454e+01 4.764e+00 -3.051 0.00244* cyl disp hp gvw accel year -3.299e-01 3.321e-01 -0.993 0.32122 7.678e-03 7.358e-03 1.044 0.29733 -3.914e-04...
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