Seabourn Legend
90.3
92.5
82.1
98.8
Seabourn Spirit
90.2
96
86.3
92
Silver Explorer
89.9
92.6
92.6
88.9
Silver Spirit
89.4
94.7
85.9
90.8
Seven Seas Navigator
89.2
90.6
83.3
90.5
Silver Whisper
89.2
90.9
82
88.6
National Geographic Explorer
89.1
93.1
93.1
89.7
Silver Cloud
88.7
92.6
78.3
91.3
Celebrity Xpedition
87.2
93.1
91.7
73.6
Silver Shadow
87.2
91
75
89.7
Silver Wind
86.6
94.4
78.1
91.6
SeaDream II
86.2
95.5
77.4
90.9
Wind Star
86.1
94.9
76.5
91.5
Wind Surf
86.1
92.1
72.3
89.3
Wind Spirit
85.2
93.5
77.4
91.9
1. SIMPLE LINEAR REGRESSION
Please explain AND use Excel
The Conde Nast Traveler Gold List for 2012 provided ratings for the top 20 small cruise ships. The dataset "Cruiseships" provides data on the following variables:
Overall: Overall score for the cruise ship
Itineraries/Schedule: Score for itineraries/schedules
Shore Excursions: Score for shore excursions
Food/Dining: Score for food/dining on board the cruise ship
a) Run a regression to estimate how the overall score depends on Food/Dining. Write out the regression equation.
b) What does the slope mean?
c) Write out the null and alternative hypotheses and test the hypothesis to come to your conclusion. i.e Do you reject the null hypothesis, and if so, what does it mean?
d) What is the R-squared value? What does it mean?
e) What would be the overall score for the cruise ship if the food/dining was scored 90.
2) MULTIPLE REGRESSION
f) Use the same dataset as problem 1. Run a multiple regression to estimate how the overall score depends on all of the other independent variables (itineraries/schedule, shore excursions, food/dining). Write out the regression equation.
g) What does the coefficient for Shore Excursions mean?
h) Which variables are statistically significant? Explain.
i) What is the R-squared value? How has it changed from the simple linear regression and why?
j) Predict the overall score for a cruise ship that has a score of 85 in itineraries/schedule, a score of 92 on shore excursions, and a score of 94 on food/dining.