The purpose of confidence of intervals is to determine a series of values from recurring samples of data so that the series of values of the specific population parameter is more likely to happen within the specified probability. Here’s my Statistics for Dummies interpretation and example.

Let’s say that the population parameter of matter is the population average and that the series of values has an 80% confidence interval. The confidence of interval is not a probability that there is 80% possibility of the confidence interval being the population average, the confidence interval is the 80% of when sampled data from the specific range of the population parameter happens again and again from the population, thus, the percentage of these intervals will have the population average.

Also, another purpose of use and why would be the amount of data that the provider believes as factual with a high degree of Confidence; that is more certain about a part of the data than perhaps some of the secondary data gathered. Confidence Intervals can be the expected range of outcome.

Confidence intervals are used to reject a null hypothesis. If I set my confidence level for my test at 80%, I have a 20% chance of being wrong about the null hypothesis. Of course I can't completely reject the possibility of being wrong. Toss a penny 100 times and it's a 50/50 chance that it's going to come up heads. The actual results may vary by five one way or the other, but still lie within the parameters. Confidence interval lets me predict how close to 50/50 the results are going to be and how often.

Confidence Intervals measure the probability of something likely to occur within a population based on the values or data gathered from repeated testing of that specific population.

For example, as in a weather prediction, if a certain weather condition presents itself and can illustrate to produce a Thunderstorm, then the confidence interval would be significant that a storm will occur.

Another Example: Surfing the Wave

In Hawaii, Surfing is a popular sport. The most most most important factor for a good day of surf is the size of a swell (wave height), the average sizes of swells throughout a given timeframe, and the consistency (ride length and wave direction) of a swell. How are Confidence Intervals used in surfing to determine wave height? Confidence Intervals measure the probability of how high and what wave direction, waves will travel at a given timeframe. By testing and gathering the data and values that a range of waves provides, including atmospheric and climate conditions, the values of these wave intervals will average a numbered wave height, providing a probability that during the same timeframe of the next day, a similar average wave height will occur.