The Science of Life

As promised last time , I will introduce the concept of hypothesis testing.  This is finally getting to the meat and potatoes of statistical analysis. There are three things that need to be true in order for a hypothesis to be held true: The data needs to be sampled randomly.  A random sample is exactly what it says on the tin; a group from the population where each individual has an equal chance of being picked. We need to know the sample mean and standard deviation . One or both of the following: Data needs to come from a normal distribution There needs to be a large sample size (for a lot of cases, at least 30, but the more the merrier). There are 5 steps for hypothesis testing from either of two methods.  Statisticians typically distinguish between whether or not we know the population standard deviation.  Realistically, this means whether we know the standard deviation for the population (everyone) or for the sample (small portion of everyone under study).  For