Free Statistics for Dummies by Deborah Jean Rumsey Page A

standard deviation to characterize it. See Chapter 8 for plenty more information on the normal distribution.
TECHNICAL STUFF 
The normal distribution is also used to help measure the accuracy of many statistics, including the mean, using an important result in statistics called the central limit theorem. This theorem gives you the ability to measure how much your sample mean will vary, without having to take any other sample means to compare it with (thankfully!). It basically says that your sample mean has a normal distribution, no matter what the distribution of the original data looks like (as long as your sample size was large enough). See Chapter 9 for more on the central limit theorem (known by statisticians as the "crown jewel of all statistics." Should you even bother to tell them to get a life?).
HEADS UP 
If a data set has a normal distribution, and you standardize all of the data to obtain standard scores, those standard scores are called Z-values. Z-values have what is known as a standard normal distribution (or Z-distribution). The standard normal distribution is a special normal distribution with a mean equal to 0 and a standard deviation equal to 1. The standard normal distribution is useful for examining the data and determining statistics like percentiles, or the percentage of the data falling between two values. So if researchers determine that the data have a normal distribution, they will usually first standardize the data (by converting each data point into a Z-value), and then use the standard normal distribution to explore and discuss the data in more detail.
    Experiments
    An experiment is a study that imposes a certain amount of control on the study's subjects and their environment (for example, restricting their diets, giving them certain dosage levels of a drug or placebo, or asking them to stay awake for a prescribed period of time). The purpose of most experiments is to pinpoint a cause-and-effect relationship between two variables (such as alcohol consumption and impaired vision). Here are some of the questions that experiments try to answer:
Does taking zinc help reduce the duration of a cold? Some studies show that it does.
Does the shape and position of your pillow affect how well you sleep at night? The Emory Spine Center in Atlanta says, "Yes."
Does shoe heel height affect foot comfort? A study done at UCLA says up to one inch heels are better than flat soles.
    In this section, you find more information about how experimental studies are (or should be) conducted. And Chapter 17 is entirely dedicated to the subject. For now, just concentrate on the basic lingo relating to experiments.
    Treatment group versus control group
    Most experiments try to determine whether some type of treatment (or important factor) has some sort of effect on an outcome. For example, does zinc help to reduce the length of a cold? Subjects who are chosen to participate in the experiment are typically divided into two groups, a treatment group and a control group. The treatment group consists of those who receive the treatment that supposedly has an effect on the outcome (in this case, zinc). The control group consists of those who do not receive the treatment, or those who receive a standard, well-known treatment whose results will be compared with this new treatment (such as vitamin C, in the case of the zinc study).
    Placebo
    A placebo is a fake treatment, such as a sugar pill. It is often given to the members of the control group, so that they will not know whether they are taking the treatment (for example, zinc) or receiving no treatment at all. Placebos are given to the control group in order to control for a phenomena called the placebo effect , in which patients who receive any sort of perceived treatment by taking a pill (even though it's a sugar pill) report some sort of result, be it positive ("Yes, I feel better already") or negative ("Wow, I amstarting to feel a bit dizzy"), due to a psychological effect.