Question

In: Statistics and Probability

Problem (simple linear regression). McDonald’s Corporation reported total revenues (X) and net profits (Y) from 1998...

Problem (simple linear regression). McDonald’s Corporation reported total revenues (X) and net profits (Y) from 1998 to 2005. Using 2-var statistics, we get: x-average=15.86; standard deviation of X =2.82; y-average=1.795, standard deviation of Y=0.5278; n=8 (from 1998 to 2005). Sum of squared X=2067.50, sum of squared Y=27.73, and sum of the product of X and Y =233.28. The least-square regression is Y (net profit) =0.2107+0.0999X (total revenue), with ESS=1.3965, and standard error of estimate (Sy,x)=0.4824. For one year with total revenue of 18.0, what is the 95% confidence interval for the net profit? (a) Compute the coefficient of determination, r-square , and interpret its meaning in the context of the problem. (b) Testing the hypothesis that the slope could be 0 at 0.10 level of significance. (c) Conduct the ANOVA F-test to the overall validity of the regression analysis. Use 0.10 level of significance.

Solutions

Expert Solution

Solution:

NOTE:: I HOPE YOUR HAPPY WITH MY ANSWER....***PLEASE SUPPORT ME WITH YOUR RATING...

***PLEASE GIVE ME "LIKE"...ITS VERY IMPORTANT FOR ME NOW....PLEASE SUPPORT ME ....THANK YOU


Related Solutions

Problem (simple linear regression). McDonald’s Corporation reported total revenues (X) and net profits (Y) from 1998...
Problem (simple linear regression). McDonald’s Corporation reported total revenues (X) and net profits (Y) from 1998 to 2005.  Using 2-var statistics, we get: x-average=15.86;  standard deviation of X =2.82;  y-average=1.795, standard deviation of Y=0.5278; n=8 (from 1998 to 2005).  Sum of squared X=2067.50, sum of squared Y=27.73, and sum of the product of X and Y =233.28. The least-square regression is Y (net profit) =0.2107+0.0999X (total revenue), with ESS=1.3965, and standard error of estimate (Sy,x)=0.4824. For one year with total revenue of 18.0, what...
Describe the each scatterplot's usefulness in terms. (x and y has simple linear regression relationship.) (Y~X)...
Describe the each scatterplot's usefulness in terms. (x and y has simple linear regression relationship.) (Y~X) 1. scatter plot of x and y 2. scatter plot of x and residuals 3. scatter plot of order of the x and residuals 4. scatter plot of yhat and residuals
6. In the simple linear regression model, the y-intercept represents the: a. change in y per...
6. In the simple linear regression model, the y-intercept represents the:a. change in y per unit change in x.b. change in x per unit change in y.c. value of y when x=0.d. value of x when y=07. In the simple linear regression model, the slope represents the:a. value of y when x=0.b. average change in y per unit change in x.c. value of x when y=0.d. average change in x per unit change in y.8. In regression analysis, the residuals...
You are developing a simple linear regression analysis model. The simple correlation coefficient between y and...
You are developing a simple linear regression analysis model. The simple correlation coefficient between y and x is -0.72. What do you know must be true about b1. The least squares estimator of B1? Why? In a multiple linear regression analysis with k = 3. From the t test associated with B1, you conclude that B1 = 0. When you do the f test will you reject or fail to reject the null hypothesis? Why? In a simple bilinear regression...
Use Excel to estimate a simple linear regression model for the following data (Y is a...
Use Excel to estimate a simple linear regression model for the following data (Y is a dependent variable and X is an independent variable): Y X 0 -2 0 -1 1 0 1 1 3 2 Fill in Multiple Blanks: What is the slope of the estimated line?  In your answer, show one (1) digit to the right of the decimal point, for example, 1.0, 1.2. Apply the appropriate rounding rule if necessary. What is the Y-intercept?
Question 3 Suppose that the estimated simple linear regression of a response Y on a predictor...
Question 3 Suppose that the estimated simple linear regression of a response Y on a predictor X based on n = 6 observations produces the following residuals: resid <- c(-0.09, 0.18, -0.27, 0.16, -0.06, 0.09) Note: For this question, all of the computations should be performed “by-hand”. (a) (1 point) What is the estimate of σ 2? (b) (2 points) Further, you know that the estimated regression parameters are βˆ 0 = −0.54 and βˆ 1 = 0.08. Additionally, the...
Given The following results from LINEAR REGRESSION Analysis for the variables X and Y Slope= 12.7...
Given The following results from LINEAR REGRESSION Analysis for the variables X and Y Slope= 12.7 y-intercept =3.2 n=10 SE=4.3 The equation of the regression line is …… and 95% confidence interval for the slope is…. (A)Y=3.2+12.7X, and (3.675,12.768) (B)Y=12.7+3.2X, and (2.784,12.745) (C)Y=3.2+12.7X, and (2.784,22.616)
If the R-square of the simple regression of Y on X is 0.5, then the hypothesis...
If the R-square of the simple regression of Y on X is 0.5, then the hypothesis that X doesnot have statistically significant effect on Y …… at the 5% level of significance. might be accepted or rejected is accepted is rejected can not be tested
In simple linear regression, at what value of the independent variable, X, will the 95% confidence...
In simple linear regression, at what value of the independent variable, X, will the 95% confidence interval for the average value of Y be narrowest? At what value will the 95% prediction interval for the value of Y for a single new observation be narrowest?
Question 4 A simple linear regression model was used in order to predict y, duration of...
Question 4 A simple linear regression model was used in order to predict y, duration of relief from allergy, from x, dosage of medication. A total of n=10 subjects were given varying doses, and their recovery times noted. Here is the R output. summary(lmod4) ## ## Call: ## lm(formula = y ~ x) ## ## Residuals: ##     Min      1Q Median      3Q     Max ## -3.6180 -1.9901 -0.4798 2.2048 3.7385 ## ## Coefficients: ##             Estimate Std. Error t value Pr(>|t|)    ## (Intercept)...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT