d above, can be written as <span class="math inline">\(K_+=\sum_{n=1}^N \mathbf{1}\{\mathbf{x}_n &gt; \mathbf{0}\}\)</span> and <span class="math inline">\(K_-=\sum_{n=1}^N \mathbf{1}\{\mathbf{x}_n &lt; \mathbf{0}\}\)</span>. We already saw that the indicator events <span class="math inline">\(\mathbf{1}\{\cdot\}\)</span> are Bernoulli distributed with success probability <span class="math inline">\(0.5^P\)</span>. Thus <span class="math inline">\(K_+\)</span> and <span class="math inline">\(K_-\)</span> ar