In this chapter, we introduce sensitivity analysis in linear programming. That is, we study the effect on the optimal solution that small changes in the statement in the problem entail. We consider changes in the objective function coefficients and changes in the constraint inequalities (which are often determined by supplies of raw materials in real life problems). The latter changes are closely tied with the notion of marginal values (shadow prices), which we also introduce and compute. We define and compute stable ranges of the values of a parameter where certain features of the solution remain unchanged. Finally, we study duality, which fits here as a topic because the decision variables in the dual problem are the marginal values of the original problem.