State Markov's inequality and Chebyshev's inequality.

Let $\mathcal{G}^{(2)}(n, p)$ denote the probability space of bipartite graphs with vertex classes $U=\{1,2, \ldots, n\}$ and $V=\{-1,-2, \ldots,-n\}$, with each possible edge $u v(u \in U,$, $v \in V)$ present, independently, with probability $p$. Let $X$ be the number of subgraphs of $G \in \mathcal{G}^{(2)}(n, p)$ that are isomorphic to the complete bipartite graph $K_{2,2}$. Write down $\mathbb{E} X$ and $\operatorname{Var}(X)$. Hence show that $p=1 / n$ is a threshold for $G \in \mathcal{G}^{(2)}(n, p)$ to contain $K_{2,2}$, in the sense that if $n p \rightarrow \infty$ then a. e. $G \in \mathcal{G}^{(2)}(n, p)$ contains a $K_{2,2}$, whereas if $n p \rightarrow 0$ then a. e. $G \in \mathcal{G}^{(2)}(n, p)$ does not contain a $K_{2,2}$.

By modifying a random $G \in \mathcal{G}^{(2)}(n, p)$ for suitably chosen $p$, show that, for each $n$, there exists a bipartite graph $H$ with $n$ vertices in each class such that $K_{2,2} \not \subset H$ but $e(H) \geqslant \frac{3}{4}\left(\frac{n}{\sqrt[3]{n-1}}\right)^{2} .$