Doctors are always seeking better treatments for their patients and behind the scenes there is a vast amount of research being conducted. Biology is subject to variation. No two people are identical not even identical twins. The way in which we respond to treatment will vary. One woman, for instance, may be happy with one oral contraceptive pill but not another.
Statistical analysis forms the basis for many conclusions in the medical sciences. It is a very exacting science and most medical schools as well as other institutions have professional medical statisticians. Most research starts by asking a question. A method of collecting relevant data (information) is planned and the results collected. Data analysis is undertaken with the purpose of answering the original question, sometimes called a hypothesis. Frequently, in research we use a placebo such as a tablet with no medicine in it to compare with a new drug (placebo & controlled trials).
Let us consider the case of a comparison of two drugs used to reduce heavy periods. Fifty women receive drug A and another fifty drug B. If forty women in each group report improvement no analysis would be required to say that the two drugs are e qually effective. If all fifty report improvement with drug ?A? and none with drug B then again it would seem fairly obvious that drug A is better than B. Clearly sometimes a symptom may resolve by itself and one must be aware that the new drug is not necessarily beneficial. If drug ?A? produces improvement in forty out of fifty patients and drug B is associated with improvement in twenty out of fifty a statistician could calculate the likelihood of this happening by chance. This is usually expressed as a p (probability) value. Usually we accept that if the chance of the difference in results is less than one-in-twenty (p<0.05; 5 out of 100) the findings are significant. There will often be a number of studies addressing the same question and they will each have their own unique set of data. The larger the amount of data collected in the study the more powerful the results. Frequently different studies come to conflicting conclusions.
   
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