Question

In: Statistics and Probability

B.   Regression Analysis: Avg. Tot. Score versus PPS, %Takers Model Summary      S   R-sq  R-sq(adj)  R-sq(pred) 32.4595  81.95%     81.18%  &nbs


B.   Regression Analysis: Avg. Tot. Score versus PPS, %Takers

Model Summary

     S   R-sq  R-sq(adj)  R-sq(pred)

32.4595  81.95%     81.18%      79.59%

Coefficients

Term       Coef  SE Coef  T-Value  P-Value   VIF

Constant  993.8     21.8   45.52   0.000

PPS 12.29     4.22     2.91   0.006 1.54

%Takers  -2.851   0.215   -13.25   0.000 1.54

1.       Give a correct interpretation of the slope of PPS in Model B.

2.      What is the fit in Model B for a state with $5500 in per pupil spending and 60% of eligible students (%Takers) taking the exam?

Regression Analysis: Overall Rating versus Itineraries/Schedule, Shore Excursions, Food/Dining

Model Summary

     S   R-sq  R-sq(adj)  R-sq(pred)

1.38775  74.98%     70.29%      58.09%

Coefficients

Term Coef  SE Coef  T-Value  P-Value   VIF

Constant 35.6     13.2    2.69   0.016

Itineraries/Schedule   0.110   0.130     0.85   0.407 1.05

Shore Excursions      0.2445  0.0434     __ ___    1.07

Food/Dining 0.2474   0.0621   3.98 0.000 1.01

1.      What are the missing T-Value and P-Value for Shore Excursions?  Show calculations and explain your answer(s).

2.      Which of the following statements below are true?  (Select all that are true and briefly explain your answer(s).)

A.    If Itineraries/Schedule is removed from the model, the multiple R-squared will increase.

B.     If Itineraries/Schedule is removed from the model, the adjusted R-squared will increase.

C.     If Itineraries/Schedule is removed from the model, the multiple R-squared will decrease.

D.    If Itineraries/Schedule is removed from the model, the adjusted R-squared will decrease.

3.      What is the predicted rating for a cruise which rates 50 on Itineraries/Schedule, 70 on Shore Excursions, and 75 on Food/Dining?

4.      As the cruise coordinator, how might you make use of these regression results?

Solutions

Expert Solution

Give a correct interpretation of the slope of PPS in Model B.

One unit increase in PPS, increse the Avg. Tot. Score to by 12.29

2. What is the fit in Model B for a state with $5500 in per pupil spending and 60% of eligible students (%Takers) taking the exam?

Regression equation

Avg. Tot. Score= 993.8 + 12.29 PPS - 2.851 % of takers

If percent is taken as whole number
Avg. Tot. Score= 993.8 + 12.29(5500) - 2.851 (60) = 68417.74

If percent is taken as decimal number
Avg. Tot. Score= 993.8 + 12.29(5500) - 2.851 (.60) = 68587.0894

1. What are the missing T-Value and P-Value for Shore Excursions? Show calculations and explain your answer(s).

tvalue = coeff/se coeffi = 0.2245/0.0434=5.6336

pvalue need the number of observation
tstat(5.336,n-2)

2. Which of the following statements below are true? (Select all that are true and briefly explain your answer(s).)

B. If Itineraries/Schedule is removed from the model, the adjusted R-squared will increase.

adjusted R is calculated by penalizing Rsquare value for any insignificant variables. On removing the insignificant variable, adjusted R will increase.

3. What is the predicted rating for a cruise which rates 50 on Itineraries/Schedule, 70 on Shore Excursions, and 75 on Food/Dining?

y = 35.6+0.11 itineraries/Schedule +
0.2445   Shore Excursions +0.2474   Food/Dining

y = 35.6+0.11(50) +
0.2445(70) +0.2474(75)= 76.77

4. As the cruise coordinator, how might you make use of these regression results?
cruise coordinator must work on improving the rating for Shore Excursions and Food/Dining


Related Solutions

Using Minitab to calculate the regression analysis: avg tot. score vs pps. Then, Compute and interpret...
Using Minitab to calculate the regression analysis: avg tot. score vs pps. Then, Compute and interpret a 95% confidence interval for the population slope. State PPS T/S Ratio Avg. Salary %Takers Avg. Tot. Score "Alabama"        4.405 17.2 31.144 10 1035 "Alaska"         8.963 17.6 47.951 48 939 "Arizona"        4.778 19.3 32.175 28 950 "Arkansas"       4.459 17.1 28.934 7 1010 "California"     4.992 24 41.078 46 908 "Colorado"       5.443 18.4 34.571 31 985 "Connecticut"    8.817 14.4 50.045 82 914 "Delaware"       7.03 16.6 39.076...
Model Summary S R-sq R-sq(adj) 1.46695 0.09% 0.00% Analysis of Variance Source DF SS MS F...
Model Summary S R-sq R-sq(adj) 1.46695 0.09% 0.00% Analysis of Variance Source DF SS MS F P Regression 1 0.0160 0.01597 0.01 0.933 Error 8 17.2156 2.15195 Total 9 17.2316 The is 0.3 Correlation Coefficient <<<<<<<<<<<<<< Does the Correlation Coefficient justify your answer to #22 or would you now change your answer? Why or why not? What does the Correlation Coefficient tell you about the direction and strength of the relationship between these variables? Using the P value or the...
18-E3. Results of multiple regression for expend Summary measures Adj R-Square 71.5% Model Error 4.877 Regression...
18-E3. Results of multiple regression for expend Summary measures Adj R-Square 71.5% Model Error 4.877 Regression coefficients Coefficient Std Err t-value P-value Constant -7.53 4.27 -1.76 0.08 Age 3.786 0.260 14.56 0.000 Age 2 -0.041 0.004 -10.72 0.000 What is the formula relating salary to age? What would be the predicted salary of someone of age 30? According to this model, what age is associated with the highest salary? How well can you predict salary from someone’s age alone? If...
The following is a regression summary from R for a linear regression model between an explanatory...
The following is a regression summary from R for a linear regression model between an explanatory variable x and a response variable y. The data contain n = 50 points. Assume that all the conditions for SLR are satisfied. Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -1.1016 0.4082 -2.699 -------** x 2.2606 0.0981 ---- < 2e-16 *** (a) Write the equation for the least squares regression line. (b) R performs a t-test to test whether the slope is significantly...
The R output below gives the summary of the multiple regression model for birth weight based...
The R output below gives the summary of the multiple regression model for birth weight based on both gestation length and smoking status: lm(formula = Weight ~ Weeks + SmokingStatus, data = births) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -1724.42 558.84 -3.086 0.00265 ** Weeks 130.05 14.52 8.957 2.39e-14 *** SmokingStatusSmoker -294.40 135.78 -2.168 0.03260 * --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 484.6 on 97 degrees...
Use regression analysis to estimate the market model for Company A and Company B, and the equally weighted portfolio.
  Use regression analysis to estimate the market model for Company A and Company B, and the equally weighted portfolio. a. Interpret the regression slope coefficient (beta) in the context of the market model for each of the 3 assets. b. Interpret the coefficients of determination (R2) in the context of the market model (systematic and nonsystematic risk). The calculations can be done with Excel’s Data Analysis “Regression” function, clicking on “Line Fit Plots” in the dialogue box to see...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT