Chebyshev inequality problem

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I'm trying to solve following problem:

The symmetric coin is tossed 1600 times. What is the probability that the head will be shown up more than 1200 times?

As I know, I should use Chebyshev inequality, but I could not find mean and variance. Can you help me?

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Consider random variable $X$ which is a number of times that head was show up. So, if we denote as $\xi_i$ the showing of head in $i$-th experiment, we will have

$$X = \sum_{i=1}^{1600}\xi_i.$$

The expectation is linear over them, so $$E(X) = E\left(\sum_{i=1}^{1600}\xi_i\right)=\sum_{i=1}^{1600}E(\xi_i) = \sum_{i=1}^{1600}\frac12 = 800.$$

All of the experiments are independent from each other, so the variance will be linear as well

$$\text{Var}(X) = \text{Var}\left(\sum_{i=1}^{1600}\xi_i\right)=\sum_{i=1}^{1600}\text{Var}(\xi_i) = \sum_{i=1}^{1600}\frac12\left(1-\frac12\right) = 400.$$

So, now you are able to apply Chebyshev inequality. Do you need further help with Chebyshev inequality?