Probability distributions. The values of a random variable can be summarized in a frequency distribution called a probability distribution. Three such distributions are impoant in medicine; Binomial and Poisson distributions are discrete probability distributions of a variable that can have only two outcomes (yes or no). The associated random variable can take only integer values, 0,1,2,3...n. Normal (Gaussian) distribution is continuous, so it can take on any values. The curve is inveed, bell shaped and smooth. The peak represents the mean, median and mode all of which coincide. The variation is measured by standard detion. The area under the curve is equal to 1(because it is a probability distribution). The area on the left half of the mean is equal to the area on the right half of the mean. We use the standard normal distribution curve, which has a mean of 0 and a standard detion of 1. It is also called the z-distribution. 68.2% of all values lie between -1 and + 1 SD around the mean. 95.4% of all values lie between -2 and +2 SD. Poisson's Distribution In probability theory and statistics Poisson distribution is a discrete probability distribution that expresses the probability of a number of events occurring in a fixed period of time if these events occur with a known average rate and independently of the time since the last event. It can also be used for the number of events in other specified intervals such as distance, area or volume. The distribution was discovered by Simeon Denis Poisson. The work focused on ceain random variables N that count, among other things, a number of discrete occurrences (sometimes called arrivals) that take place during a time interval of given length. Therefore, as per the description provided, the answer is 50%. Ref : 1) Park's Textbook of Preventive and Social Medicine; 18th edition; Page-647 2) Principles of community medicine by B. Sridhar Rao; 5th edition; Page-63