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Regression Analysis 137 and actual sales (column 3). This difference (positive or negative) is referred to as the estimation err ...
As the term suggests, ordinary least-squares regression computes coefficient values that give the smallest sum of squared errors ...
Regression Analysis 139 MULTIPLE REGRESSION Because price is not the only factor that affects sales, it is natural to add other ...
Table 4.5 lists the predictions, prediction errors, and squared errors for this regression equation. The equation’s sum of squar ...
Regression Analysis 141 Management believes price changes will have an immediate effect on ticket sales, but the effects of inco ...
Clearly, R^2 always lies between zero and one. If the regression equation pre- dicted the data perfectly (i.e., the predicted an ...
Regression Analysis 143 The difference between R^2 and is the adjustment for the degrees of free- domin the latter. One can show ...
of F to be 3.49 and 5.95, respectively. Since F is larger than 5.95, we can reject the hypothesis of zero coefficients with 99 p ...
Regression Analysis 145 errors greater than zero. We appeal to the exact distribution of the t-statistic to pinpoint the degree ...
STANDARD ERROR OF THE REGRESSION Finally, the standard error of the regressionprovides an estimate of the unexplained variation ...
Regression Analysis 147 OMITTED VARIABLES A related problem is that of omitted variables. Recall that we began the analysis of a ...
Such settings are called perfectly competitive markets, which we will discuss in detail in Chapter 7. For now, note that price a ...
Regression Analysis 149 FIGURE 4.2 Shifts in Supply and Demand The scatter of points in parts (a) and (b) is caused by shifts in ...
Here, we have added the term e. This random term indicates that sales depend on various variables plus some randomness. The stat ...
Forecasting 151 future economic developments. (The stock market is one of the best-known leading indicators of the course of the ...
FIGURE 4.3 The Component Parts of a Time Series A typical time series contains a trend, cycles, seasonal variations, and random ...
Forecasting 153 business cycles. Although we do not show the random fluctuations, we can describe their effect easily. If we too ...
154 Chapter 4 Estimating and Forecasting Demand FIGURE 4.4 Fitting a Trend to a Time Series Candidates include linear and nonlin ...
Forecasting 155 A positive value of the coefficient c implies an increasing rate of growth in sales over time; that is, sales te ...
In 1977, Company A’s common stock sold for $50 per share, the same price as a share of Company B’s stock. Over the next 35 years ...
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