diff --git a/projects/project2/main.pdf b/projects/project2/main.pdf
index 239d2fd..41f6c95 100644
Binary files a/projects/project2/main.pdf and b/projects/project2/main.pdf differ
diff --git a/projects/project2/main.tex b/projects/project2/main.tex
index 10257dc..f042430 100644
--- a/projects/project2/main.tex
+++ b/projects/project2/main.tex
@@ -150,8 +150,7 @@ The Jacobi rotation algorithm is implemented as described in the lecture notes.
 
 \section*{Problem 5}
 \subsection*{Subproblem (a)}
-The scaling of the number of iterations is tested in \texttt{src/project2/scaling\_tester.cpp}. The results are shown in \autoref{fig:scaling}. On the logarithmic scale, we see a trend that is roughly of the order $\sqrt{\log N}$.
-
+The scaling of the number of iterations is tested in \texttt{src/project2/scaling\_tester.cpp}. The results are shown in \autoref{fig:scaling}. On the double logarithmic scale, the scaling is approximately linear, indicating a polynomial relation between the number of iterations and the matrix size $N$.
 \begin{figure}
     \centering
     \includegraphics[width=0.7\textwidth]{include/scaling_data_iterations.pdf}
diff --git a/src/project2/python/scaling_plotter.py b/src/project2/python/scaling_plotter.py
index c6cd2e0..c83e54c 100644
--- a/src/project2/python/scaling_plotter.py
+++ b/src/project2/python/scaling_plotter.py
@@ -7,6 +7,7 @@ import os
 parser = argparse.ArgumentParser(description='Plot scaling data.')
 parser.add_argument('input_file', type=str, help='Path to the input CSV file')
 parser.add_argument("--times", "-t", action="store_true", help="Plot times instead of iterations")
+parser.add_argument("--no-loglog", "-nL", action="store_true", help="Do not use log-log scale")
 
 args = parser.parse_args()
 data = pd.read_csv(args.input_file)
@@ -18,16 +19,17 @@ if args.times:
     ax.plot(x, data["Arma_time"], label='Armadillo Time', color='C1', linestyle='-', marker='o')
     ax.set_ylabel('Time (s)')
     ax.set_title('Scaling of Computation Time')
-    ax.set_yscale('log')
     ax.legend()
     ax.grid()
 else:
     ax.set_ylabel('Number of Iterations')
     ax.set_title('Scaling of Jacobi Iterations')
-    ax.set_yscale('log')
     ax.plot(x, data["Jacobi_iterations"], label='Jacobi Iterations', color='C0', linestyle='-', marker='o')
     ax.grid()
 
+if not args.no_loglog:
+    ax.set_xscale('log')
+    ax.set_yscale('log')
 ax.set_xlabel('Matrix Size N')
 dir = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../../projects/project2/include"))
 filename = args.input_file.split("/")[-1].replace(".txt", "")