Health care cost is an increasingly important part of the United States economy. In this exercise you are to identify variables that are predictors for the cost of physician and clinical services, either individually or in combination. Use the data file Health Care Cost Analysis, which contains annual health care costs for the period 1960–2008. As a first step you are to explore the simple relationships between physician and clinical services cost and individual variables using a combination of simple correlations and graphical scatter plots. You should also examine the changes in cost of physicians and clinical services and other variables over time. Medical care costs are, of course, affected by various national policies and changes in health care providers and health insurance practice.

Based on these analyses, develop a multiple regression model that predicts costs of physicians and clinical services. You will probably find that the model has errors that are serially correlated and this possibility should be tested for by using the Durbin-Watson test.

If serial correlation exists in your initial model then to adjust for serial correlation, you are to use the difference variables to estimate a model that predicts the change in physician and clinical services as a function of change in the predictor variables. Again, explore the simple relationship between the change in physician and clinical services and the change in the other predictor variables using correlations and scatter plots. Using these results, develop a multiple regression model using the changes in variables to predict the change in physician and clinical services costs.

Prepare a report that identifies variables that are related to cost of physicians and clinical services individually and in combination.