Approximation results and Korovkin-type theorems are important concepts in the field of mathematics, particularly in the study of approximation theory. The basic idea of approximation theory is to find a function that approximates another function with a certain degree of accuracy. Approximation results and Korovkin-type theorems are methods used to prove the convergence of a sequence of functions to a given function. Approximation results deal with the convergence of a sequence of functions to a given function. These results are important because they allow us to approximate a function by a sequence of simpler functions. The most famous example of an approximation result is the Weierstrass approximation theorem, which states that any continuous function can be approximated uniformly by a polynomial. Approximation results are used in a wide range of applications, including numerical analysis, computer graphics, and signal processing. Korovkin-type theorems are a generalization of approximation results. These theorems state that under certain conditions, a sequence of positive linear operators can converge uniformly to a continuous function. Korovkin-type theorems are used to prove the convergence of a sequence of functions to a given function, and they have applications in the study of Fourier series, interpolation theory, and spline functions. Both approximation results and Korovkin-type theorems are important tools in the study of approximation theory. They allow us to approximate complex functions by simpler ones, and they provide a theoretical framework for the study of convergence of sequences of functions. These concepts are fundamental to many areas of mathematics and have numerous practical applications in various fields. In conclusion, approximation results and Korovkin-type theorems are important concepts in the study of approximation theory in mathematics. They provide a framework for approximating complex functions by simpler ones and for studying the convergence of sequences of functions. These concepts have numerous applications in various fields, including numerical analysis, computer graphics, and signal processing.