The linear regression models examined so far have always included a constant that represents the point the regression line crosses the y-axis, called the intercept. However, there are some cases where an intercept may not conceptually apply to the data being modeled. For example, a factory cannot produce widgets if the equipment is not running, a salesperson cannot sell without any products, and so on. Although the apriori knowledge that \(y = 0\) when \(x = 0\) is not enough to completely justify regression through the origin, (Hocking, as cited in Eisenhauer) the resulting linear