For any discrete random variable X, with probability mass function P(X = j) = pj, pj ≥ 0, j ∈ {0,….,N}, and \(\mathop \sum \limits_{j = 0}^N {p_j} = 1\), define the polynomial function \({g_x}\left( z \right) = \;\mathop \sum \limits_{j = 0}^N {p_j}{z^j}\). For a certain discrete random variable Y, there exists a scalar β ∈ [0, 1] such that gγ (z) = (1 - β + β z)N. The expectation of Y is

• A. Nβ (1 – β)
• B. Nβ
• C. N (1 - β)
• D. Not expressible in terms of N and β alone