How to solve "x" values for quadratic equation with varying "y" values

I use a standard curve to find concentrations of solutions based on absorbance values. My standard curve best fit is a second order polynomial. I want to use matlab to solve this quadratic equation where the x values are concentrations using the y values which are absorbance.

For example, my standard curve equation is in the form of x^2+2x+1= y, where there are over a 100 y values. Can I use matlab to find the x values for the data set of y values?

I tried importing my data and saved it as var1 and used this command:

>> solve(x + 1 == VarName1 ,x)

It gave me:

Warning: 5 equations in 1 variables.

In C:\Program Files\MATLAB\R2013a\toolbox\symbolic\symbolic\symengine.p>symengine at 56

In mupadengine.mupadengine>mupadengine.evalin at 97

In mupadengine.mupadengine>mupadengine.feval at 150

In solve at 170

Warning: Explicit solution could not be found.

> In solve at 179

ans =

[ empty sym ]

Answer 1

[Star Strider]

It’s not easy to visualise what you’re doing, so I’m making a guess with this. Note that for it to work, your ‘y’-data have to be organised in columns. This routine should estimate the ‘x’ values for each vector of ‘y’ values:

x = repmat(1:5, 5, 1);                          % Create ‘x’ Data
y = x.^2 + 2*x + 1 + 0.1*randn(size(x));        % Create ‘y’ Data + Noise With ‘y’-Data In Columns

yf = @(x) x.^2 + 2*x + 1;                       % Objective Function

for k1 = 1:size(y,2)
    SSECF = @(b) sum((y(:,k1) - yf(b)).^2);     % Sum-Squared-Error Cost Function
    [X(k1), SSE(k1)] = fminsearch(SSECF, 1);    % Estimate ‘X’, Return Sum-Squared-Error
end