A confidence interval (CI) refers to the amount of uncertainty associated with a sample population estimate (the mean or proportion) of a true population. For example, if you are 95 percent confident that your population mean is between 75 and 100, the 95 percent confidence interval does not mean there is a 95 percent chance the mean falls within your calculated range. Interpreting confidence levels and confidence intervals. Similarly for the second group, the confidence interval for the mean is (12.1,21.9). The 95 percent confidence interval for the first group mean can be calculated as: 9±1.96×2.5 where 1.96 is the critical t-value. A confidence interval is a range of values that describes the uncertainty surrounding an estimate. Interpreting confidence level example. A confidence interval does not indicate the probability of a particular outcome. A confidence interval (or confidence level) is a range of values that have a given probability that the true value lies within it. Confidence Intervals for Unknown Mean and Known Standard Deviation For a population with unknown mean and known standard deviation , a confidence interval for the population mean, based on a simple random sample (SRS) of size n, is + z *, where z * is the upper (1-C)/2 critical value for the standard normal distribution.. If you know the standard deviation for a population, then you can calculate a confidence interval (CI) for the mean, or average, of that population. Interpreting confidence level example. A 95% confidence interval (CI) of the mean is a range with an upper and lower number calculated from a sample. These confidence intervals are used to estimate a number of different parameters. Confidence intervals for proportions. Effectively, it measures how confident you are that the mean of your sample (the sample mean) is the same as the mean of the total population from which your sample was taken (the population mean). A narrow confidence interval enables more precise population estimates. We indicate a confidence interval by its endpoints; for example, the 90% confidence interval for the number of people, of all ages, in poverty in the United States in 1995 (based on the March 1996 Current Population Survey) is "35,534,124 to 37,315,094." When a statistical characteristic that’s being measured (such as income, IQ, price, height, quantity, or weight) is numerical, most people want to estimate the mean (average) value for the population. […] Although these aspects are different, all of these confidence intervals are united by the same overall format. The confidence interval is the plus-or-minus figure usually reported in newspaper or television opinion poll results.For example, if you use a confidence interval of 4 and 47% percent of your sample picks an answer you can be “sure” that if you had asked the question of the entire relevant population between 43% (47-4) and 51% (47+4) would have picked that … The confidence interval for the first group mean is thus (4.1,13.9). Next lesson. This is the currently selected item. It's … Confidence interval simulation. If you're behind a web filter, please make sure that the domains *.kastatic.org and *.kasandbox.org are unblocked. Note: This interval is only exact when the … If multiple samples were drawn from the same population and a 95% CI calculated for … The confidence interval is a way to show what is the uncertainty within a certain statistic. Sort by: Top Voted. The width of the confidence interval is a function of two elements: Confidence level; Sampling error; The greater the confidence level, the wider the confidence interval. Because the true population mean is unknown, this range describes possible values that the mean could be. Confidence Intervals. Notice that the two intervals overlap.