Opening this file as described in Chapters 1 and 2 yields the following screen Observations on SALES, PRICE and ADVERT for 75 cities are available in the file andy.wfl.

While performing these tasks we reinforce some of the EViews steps described in earlier chapters as well as introduce some new ones. In this Chapter we use EViews to estimate this model, to obtain forecasts from the model, to examine the covariance matrix and standard errors of the estimates, and to compute confidence intervals and hypothesis test values for each of the coefficients. SALES = E(SALES) + e = ОІ 1 + ОІ 2PRICE + ОІ 3 ADVERT + e

The model includes two explanatory variables and a constant and is written as Advertising expenditure for each city A = ADVERT is also measured in thousands of dollars. Monthly sales revenue for a given city is denoted by S = SALES and measured in $1,000 units. The prices charged in a given city are collected together into a weighted price index that is denoted by P = PRICE and measured in dollars. Big AndyвЂ™s sales revenue depends on the prices charged for hamburgers, fries, shakes, and so on, and on the level of advertising. The example used in this chapter is a model of sales for Big AndyвЂ™s Burger Barn. As such it is a simple but important extension that makes linear regression quite powerful. The multiple linear regression model expands the number of explanatory variables. In the simple linear regression model the average value of a dependent variable is modeled as a linear function of a constant and a single explanatory variable.

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