An Economist Is Analysing the Incomes of Professionals (Physicians, Dentists $y = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 3 } + \varepsilon$

An economist is analysing the incomes of professionals (physicians, dentists and lawyers). He realises that an important factor is the number of years of experience. However, he wants to know if there are differences among the three professional groups. He takes a random sample of 125 professionals and estimates the multiple regression model: $y = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 3 } + \varepsilon$ .
where
y
= annual income (in $1000). $x _ { 1 }$ = years of experience. $x _ { 2 }$ = 1 if physician.
= 0 if not. $X _ { 3 }$ = 1 if dentist.
= 0 if not.
The computer output is shown below.
THE REGRESSION EQUATION IS $y =$ $71.65 + 2.07 x _ { 1 } + 10.16 x _ { 2 } - 7.44 x _ { 3 }$ . $$\begin{array} { | c | r r r | } \hline \text { Predictor } & \text { Coef } & \text { SDev } & T \\\hline \text { Constant } & 71.65 & 18.56 & 3.860 \\x _ { 1 } & 2.07 & 0.81 & 2.556 \\x _ { 2 } & 10.16 & 3.16 & 3.215 \\x _ { 3 } & - 7.44 & 2.85 & - 2.611 \\\hline\end{array}$$ S = 42.6 R-Sq = 30.9%. $$\begin{array}{l}\text { ANALYSIS OF VARIANCE }\\\begin{array} { | l | r c c c | } \hline \text { Source of Variation } & d f & \text { SS } & M S & F \\\hline \text { Regression } & 3 & 98008 & 32669.333 & 18.008 \\\text { Error } & 121 & 219508 & 1814.116 & \\\hline \text { Total } & 124 & 317516 & & \\\hline\end{array}\end{array}$$ Do these results allow us to conclude at the 1% significance level that the model is useful in predicting the income of professionals?