# Confidence level and interval relationship

### Confidence Intervals & Hypothesis Testing (1 of 5)

There is an extremely close relationship between confidence intervals and hypothesis testing. When a 95% confidence interval is constructed, all values in the. When you put the confidence level and the confidence interval together, you However, the relationship is not linear (i.e., doubling the sample size does not. So as your confidence level increase, your confidence interval gets wider. By the way, there's nothing stopping you from having 96%, 91% or even an %.

**confidence interval vs confidence levels**

In the example above, the student calculated the sample mean of the boiling temperatures to be As the level of confidence decreases, the size of the corresponding interval will decrease. This is because the standard deviation decreases as n increases. The margin of error m of a confidence interval is defined to be the value added or subtracted from the sample mean which determines the length of the interval: Suppose in the example above, the student wishes to have a margin of error equal to 0.

Confidence Intervals for Unknown Mean and Unknown Standard Deviation In most practical research, the standard deviation for the population of interest is not known.

## Confidence Intervals and Levels

In this case, the standard deviation is replaced by the estimated standard deviation salso known as the standard error. Since the standard error is an estimate for the true value of the standard deviation, the distribution of the sample mean is no longer normal with mean and standard deviation.

Instead, the sample mean follows the t distribution with mean and standard deviation.

The t distribution is also described by its degrees of freedom. For a sample of size n, the t distribution will have n-1 degrees of freedom. The notation for a t distribution with k degrees of freedom is t k.

As the sample size n increases, the t distribution becomes closer to the normal distribution, since the standard error approaches the true standard deviation for large n. Example The dataset "Normal Body Temperature, Gender, and Heart Rate" contains observations of body temperature, along with the gender of each individual and his or her heart rate. This value is approximately 1.

The estimated standard deviation for the sample mean is 0. Data presented in Mackowiak, P. For some more definitions and examples, see the confidence interval index in Valerie J. Search Confidence Intervals and Levels The confidence interval is the plus-or-minus figure usually reported in newspaper or television opinion poll results. The confidence level tells you how sure you can be. It is expressed as a percentage and represents how often the true percentage of the population who would pick an answer lies within the confidence interval.

### Interpreting confidence levels and confidence intervals (article) | Khan Academy

The wider the confidence interval you are willing to accept, the more certain you can be that the whole population answers would be within that range. Factors that Affect Confidence Intervals There are three factors that determine the size of the confidence interval for a given confidence level. Sample Size The larger your sample, the more sure you can be that their answers truly reflect the population. This indicates that for a given confidence level, the larger your sample size, the smaller your confidence interval.

However, the relationship is not linear i. Percentage Your accuracy also depends on the percentage of your sample that picks a particular answer.

It is easier to be sure of extreme answers than of middle-of-the-road ones. You should also use this percentage if you want to determine a general level of accuracy for a sample you already have. To determine the confidence interval for a specific answer your sample has given, you can use the percentage picking that answer and get a smaller interval.