A Data Analyst for a Small Chain of Boutique Hotels

A data analyst for a small chain of boutique hotels was interested in what shaped guest satisfaction with their hotel stays. He decided to build a multi-level linear model. Because he had not run one before he decided to build the model in stages, starting with a basic linear model. His outcome variable was Satisfaction, which measured guest satisfaction on a ten-point scale. His initial parameters were Satisfactionx (guests' satisfaction with the hotel chain prior to them staying, measured on a ten-point scale) and Duration (measuring duration of each guest's stay in days) . He ran the model and found that Satisfaction2 had a p = 0.05 (b = -1.69) and Duration had a p = 0.01 (b = 0.665) . How would you interpret this?

A) Guest satisfaction is not significantly associated with duration of stay
B) Guest satisfaction is significantly associated with duration of stay
C) Guest satisfaction significantly improves with duration of stay
D) Guest satisfaction significantly declines with duration of stay