ABSTRACT
This chapter introduces simple MA method, single exponential smoothing method, and Multiplicative Holt-Winters method. Some time series in the hospitality industry are weekly average RevPAR, daily occupancy rate, daily casino slot coin-in, weekly casino table drop, daily number of guests served, daily stock price, etc. To model and analyze a time series, it is important to understand the unique characteristics of the data. Given that seasonality is one of the main characteristics of the hospitality industry, seasonal variations are particularly obvious in hospitality time-series data.Regression analysis that examines the relationship between two variables is called simple regression, and regression analysis that contains two or more IVs is multiple regression. Regression analysis can be used for causal forecasting and time series forecasting and this section focuses on the latter. Box-Jenkins procedure is considered accurate in model fitting because it models both lagged dependent variable and estimation error residuals.
