Trends in global temperature anomalies from the past half century are investigated. To account for the seasonality of the data, a statistical model that includes monthly intercept and slope terms will be developed. Atmospheric CO2 concentrations, sunspot numbers, and various global pressure oscillations will also be included in the model. Least squares estimates of all parameters in the model will be derived, as will standard errors that account for temporal correlations in the data. To this end, standardized residuals will be modeled using an autoregressive moving average (ARMA) model. Derived standard errors will be based on the fitted ARMA model.