Finding an intercept on percentage based data and using dummy variables How do I find an intercept on a percentage data? My data has percentage of grades ( I have converted to numbers where $A^*=8, A=7,B=6...U=0$) by ethnicity and other indicators which I want to test for using dummy variables. For example 90.3% of Chinese students got $A^*-C$ grade, Mixed race students got 87.3% etc. How do I interpret this to get an intercept? I have chosen the median 32.5 as the grades are 5 $A^*$ to $C$ (between $A^*(8\cdot5=40)$ and $C( 5\cdot5=25)$. Is the use of median in this case sensible? 

My equation is going to be 

$y =b_0 +b_1 +b_2+b_3+b_4+b_5+b_6+u$

where $y$ is the grade, $b_0$ is the median ( constant), $b_1$ is the free school meal, $b_2$ is Chinese, $b_3$ is Black, $b_4$ is Asian, $b_5$ is male,    $b_6$ is female, and $u$ is the error term.
White is the default.

Therefore if a Chinese male pupil does not get free school meals(proxy for poverty)it is $b_0 + b_2 + b_5$.

My question is as above, does my use of median make any sense and secondly since I already know that Chinese pupils perform better than the rest of the group do I need to use the percentage difference or use the dummy binary variables.

I want to simply find out the effect of poverty and race on the pupils expected grades. I do not have access to individual grades or panel data for income etc hence why I want to use the free school meal.

Thanks again for your answers.

Please see image below.
As Jamzy noted, run an OLS regression on grades against whatever variables you have.

$$\text{grades} = \beta_0 + \beta_1 x_1 + \cdots + \beta_i \ \text{race} + \cdots$$

$$\text{race} =\begin{array}{cc}
  \Bigg\{ &amp; 
    \begin{array}{cc}
      0 &amp; mixed \\
      1 &amp; Chinese \\
    \end{array}
\end{array}$$

or vice versa with the 0 and 1. $\beta_0$ will be your intercept that you are looking for. If it ends up negative, try taking the log of both sides and see if a linear regression still has a good fit for you there.