diff --git a/polynomial_fit.ipynb b/polynomial_fit.ipynb
index 0e06c26..f497178 100644
--- a/polynomial_fit.ipynb
+++ b/polynomial_fit.ipynb
@@ -270,7 +270,7 @@
    "id": "b10f5bf9",
    "metadata": {},
    "source": [
-    "> **Exercise**:  Try changing the basis functions to Legendre polynomials and see how that improves the fit, both for the inversion and SVD methods. How do the results change when you change the number of data points and the order of the polynomial? Hint: You can use [`numpy.polynomial.legendre.legvander`](https://numpy.org/devdocs/reference/generated/numpy.polynomial.legendre.legvander.html) to generate the design matrix $\\mathbf{A}$ for you."
+    "> **Exercise**:  Try changing the basis functions to Legendre polynomials and see how that improves the fit, both for the inversion and SVD methods. How do the results change when you change the number of data points and the order of the polynomial? Check also how the condition number of the design matrix changes as a function of the polynomial degree when you change the polynomials you are using to fit. Hint: You can use [`numpy.polynomial.legendre.legvander`](https://numpy.org/devdocs/reference/generated/numpy.polynomial.legendre.legvander.html) to generate the design matrix $\\mathbf{A}$ for you."
    ]
   }
  ],