P values and confidence intervals are reported in almost all scientific writings and are used in interpreting results of statistical analysis. It is usual for medical researchers and other investigators to ask questions such as ‘Is the result significant?’ or ‘what is the p value?’ Many clinicians worry when they carry out statistical analysis and there are no significant results. This article describes some facts about the p value and confidence intervals.
The reporting of p values and confidence intervals usually follows hypothesis testing or significance testing.
Most scientific investigations involve the testing of hypotheses. These are formal procedures for testing
whether findings from the investigations are compatible with a so called null hypothesis. Hypotheses
refer to statements concerning the situation being investigated which are usually stated as two mutually
exclusive options; a null hypothesis and an alternative hypothesis. The null hypothesis is a statement of no
association between variables or no difference in means of groups while the alternative hypothesis states that
there’s a difference or an association. The interests of medical researchers are varied and research questions
result in statement of hypotheses. Examples of such questions are: Is there a significant difference in
proportion of low birth weight babies delivered to mothers with single and multiple pregnancies?
Is there a difference in effects of three antiretroviral drugs on reduction in viral load? ; Is there a correlation between body mass index and systolic blood pressure; or is there a difference in reduction in blood sugar between
a standard hypoglycemic and a new drug. The null hypothesis for the last study objective will be ‘There is
no correlation between body mass index and systolic blood pressure’. The use and interpretation of p values
and confidence intervals will now be discussed.