First thing, you could have mentioned, what RK method you have used. Here is a brief introduction to RK methods and Euler method, working, there merits and demerits. **Euler method** Euler's method is first order method. It is a straight-forward method that estimates the next point based on the rate of change at the current point and it is easy to code. It is a single step method. Notably, Forward Euler's method is unconditionally unstable for un-damped oscillating systems (such as a spring-mass system or wave equations) in space desctretization. For complex problems and/or boundary condition it may fail. It can be used for basic numerical analysis. This method is not commonly used for spatial discretization but some times used in time discretization. This scheme is not recommended for hyperbolic differential equation because this is more diffusive. Order of convergence of this scheme with grid refinement is very poor. Extending Euler method to higher order method is easy and straight forward. **RK methods:** Runge-Kutta methods are actually a family of schemes derived in a specific style. You can refer this link to get a basic idea of RK methods: [http://web.mit.edu/10.001/Web/Course_Notes/Differential_Equations_Notes/node5.html][1] The forward Euler method is actually the simplest RK method (1 stage, first order). Higher order accurate RK methods are multi-stage because they involve slope calculations at multiple steps at or between the current and next discrete time values. The next value of the dependent variable is calculated by taking a weighted average of these multiple stages based on a Taylor series approximation of the solution. The weights in this weighted average are derived by solving non-linear algebraic equations which are formed by requiring cancellation of error terms in the Taylor series. Developing higher order RK methods is tedious and difficult without using symbolic tools for computation. The most popular RK method is RK4 since it offers a good balance between order of accuracy and cost of computation. RK4 is the highest order explicit Runge-Kutta method that requires the same number of steps as the order of accuracy (i.e. RK1=1 stage, RK2=2 stages, RK3=3 stages, RK4=4 stages, RK5=*6 stages*, ...). Beyond fourth order the RK methods become relatively more expensive to compute. **Answer** - Usually error in Euler method is higher than higher order RK method (RK2, RK3, etc.), because truncation error in higher order methods is less compared to Euler method. - In some of the beginner level literature in numerical methods, it is wrongly mentioned that higher order methods (say, RK4) give less error than lower order method (say, Euler method). Most of the time this is true, but not all the time. This property depends on the mesh and initial condition and differential equations you have considered. - If the exact solution to the differential equation is a polynomial of order $n$, it will be solved exactly by an $n$-th Runge-Kutta method. For example, forward Euler will be exact if the solution is a line. RK4 will be exact if the solution is a polynomial of degree 4 or less. - Initial error in RK4 method is higher than Euler method for coarse grid and reduces with refining grid, because convergence rate of RK4 method is more than Euler. Please note that coarseness or fineness of grid is completely based on differential equation, initial condition and numerical scheme. You can try this experiment in your code with different differential equations, different number of grids with Euler and RK4 if you have enough time. Order of convergence of scheme can be find out by calculating slope of plot - $log(error)$ vs $log(grid size)$. [1]: http://web.mit.edu/10.001/Web/Course_Notes/Differential_Equations_Notes/node5.html