Question

Question B: 3*3 = 9 points: In service businesses, when a situation that might lead to a dissatisfied customer arises, service recovery techniques are often used. Such techniques involve, for example, complimentary desserts in restaurants or vouchers for free future stays in hotels. A leading airline is evaluating the effect of four service recovery techniques and has taken a random sample of customers who have experienced a service failure. The customers fell into three classes - frequent business travelers, occasional business travelers and leisure travelers. Across these classifications four service recovery techniques had been attempted - I (complimentary class upgrade), II (25,000 complimentary frequent flyer miles, III ($200 credit towards future air travel) and IV (no recovery). Customers had indicated (on a scale of 1-100) their willingness to consider the airline for future travel. Data from the sample are provided in the following table: Recovery Technique II 84 Traveler Type I III IV 62 97 78 A В 56 73 69 51 С 62 60 77 45 3. Conduct a one-way ANOVA with Recovery Technique as your treatment effect. Clearly mention your null and alternate hypotheses, calculations and your conclusion 4. Conduct a randomized complete block ANOVA with Traveler Type as your blocking effect. Clearly mention conclusion null and alternate hypotheses, calculations and your your 5. How do results change from (3) to (4)? Why? R

I need the R codes for these in order to solve

Answer 1

Answer:

(3)

group<-c(rep("I",3),rep("II",3),rep("III",3),rep("IV",3))
data <- c(62,56,60,84,73,60,97,69,77,78,51,45)
a1<-aov(data~group)
summary(a1)

summary(a1)
          Df Sum Sq Mean Sq F value    Pr(>F)
group           3 1087 362.4 2.162 0.171
Residuals    8     1341 167.

p-value = 0.171 > 0.05

we fail to reject the null hypothesis.