A coin is fair if the probability it will land heads on any given flip is p=1/2=50%. We flip the coin at random 400 times; it happens to land heads 232 times. That is, it landed heads on 58% of the flips. Suppose we want to test the null hypothesis that this is different from 50% just by chance. Round your values to three decimal places. If the null hypothesis is right, then the expected value of the number of heads in 400 random flips is with a standard error of . The observed number of heads here is . If the null hypothesis is right, then the expected value of the proportion of heads in 400 random flips is with a standard error of . The observed proportion of heads here is . The test statistic is the observed value, standardized with respect to the null hypothesis' expected value and standard error. (Also called a z-statistic.) What is it here? . The P-value (using a z-test) is approximated by the area under the standard normal curve as far or farther than the z-statistic (on one side). What is it here?