1. The problem statement, all variables and given/known data An observation X has density function: f(x,/theta)=6x/(t^3)*(t-x) where t is a parameter: 0<x<t. Given the single observation X, determine the maximum likelihood estimator for t. 2. Relevant equations Included below 3. The attempt at a solution For a sample size of n, the likelihood function is L(t)=product[6x_i/(t^3)*(t-x_i)] from i=1 to n. To maximize a product, we take the log L[t] and differentiate with respect to t and equate to 0. d/dt [Log[t]=3/t+Sum[1/(t-x_i)] for i=1 to n. However, I don't know how to solve 3/t+Sum[1/(t-x_i)]=0 for t since there is a t on the denominator in the sum. Is there a way to do this? Or have I misinterpreted the question? Since the question says, "Given a single observation X" am I not supposed to take the product over n samples but rather set n=1 when finding my likelihood function L(t)=6x_i/(t^3)*(t-x_i?