95% Confidence Interval - From Poll to Research

95% Confidence Interval or CI sounds complex but we see it in our daily life.  When you hear from TV or ratio says that the recent poll done by xxx indicated that if we vote today, 55% will support President Obama, and the survey has a ±3% error.  This means that based on the poll results, the percentage of people who vote for Obama may vary from 52-58%.  The range 52-58% is statistically called 95% CI.  In fact, the poll was conducted among a group of randomly selected respondents, or random sample. The rate of 55% was computed based on reported data collected among the sampled respondents.  This random sample may represent the total population to a great extent, but it does not equal the total population. When the sampled results is used to reflect the total population, statistical method can help us to determine what would be the possible range of all people in the total population who support the president – the 95% Confidence Interval.  In common language, we say that according to the poll, 52% to 58% of people support the President.  In statistical term, we say that the 95% range means if we use this range as a scale to assess the percentage of people who support the president for 100 times, 95 times we will cover the true supporting rate of the total population.  Incidentally, the digits 9 and 5 in the 95% CI are really interesting (clinck here to see another blog).  9 and 5 are the basic characteristics of a king or a president, 5 represents middle class, 9 represent highest power.  Also, as a president, we cannot expect him/her to be perfect or 100% great, 95% would be adequate!

Come back to research, almost all the work scientists are doing is to try to study a sample and use the sample to gain insight into the whole picture of the subjects they are interested in.  Therefore, 95% CI is very important.  Since 2010, the American Medical Association imposed that all research papers include 95% CI when reporting their analytic results.