This thesis estimates the production, cost, and profit functions for North Dakota agriculture using state-level input-output quantity and price data for the period 1960-2004. A Cobb-Douglas functional form with Hick-neutral technology change is used to measure the contribution of capital, land, labor, materials, energy, and chemical inputs quantities and output quantity using the primal production function; contribution of capital quantity, land quantity, output quantity, labor price, materials price, energy price, and chemical price to cost using the dual restricted cost function; and the contribution of capital quantity, land quantity, labor price, materials price, energy price, chemical price, output price to profit using the dual restricted profit function. In contrast to previous studies, quantile regression is used to explore the linear or nonlinear relationship between the independent and dependent variable by estimating parameter coefficients at each quantile using time-series data. Empirical findings suggest the cost function is the best model to examine the relationship between input prices, output quantity and cost using quantile regression for North Dakota agriculture, Further, the quantile regression suggests a linear and non-linear relationship between cost and certain independent variables.