Lets start right with an example.
The university campus wants to know how many people eat at the cafeteria on a daily basis.
Lets say that a survey concludes that 10,000 of students eat at the cafeteria on a daily basis. This number sounds interesting - is 10,000 a good number? Is the cafeteria doing well? We have no way of knowing from this number. We need more information. This is where the confidence interval comes into play.
What is the survey then says that we are 95% confident that the between 8,000 to 10,000 students eat at the cafeteria every day. How does this sound? A 95% confidence interval is an interval generated by a process that's right 95% of the time. What if we then say that we are 70% confident that between 5,000 to 14,000 ...
This solution provides an explanation for how the concept of confidence intervals will affect conclusions drawn from survey data or information presented in the news or media.