Please provide clear steps

Exercise 4.1 (*ww - Likelihood principle and p-values (50%)). (Background) Suppose that, in a social media "FaceLook", advertisements may pop up to selected users accordingly to a deep-learning (DL) algorithm. If a selected user clicks into the advertisement, then we say that the algorithm successfully selects a correct user. Let 0 6 (0, 1) be the probability of a successful selection. Assume that a random algorithm (i.e., randomly pops up an advertisement to users) leads to a successful selection rate 0 = 15%. FaceLook would like to test the effectiveness of the DL algorithm by testing Ho : 0 = 15% against H1 : 0 > 15%. (4.1) Denote success and failures by 1 and 0, respectively. FaceLook obtains the following dataset 010 0 0 0 0 1 1 0 10 010 1. (Experiment 1) Suppose that the algorithm selects 15 users. It records 5 successes. Then it is reasonable to model the number of successes by X ~ Bin(15, 0), whose PMF is fo = (15)0 (1 -0)15-=1(x = 0, . . ., 15). (a) (10%) Derive the likelihood function L(0 | X)