The probability that an interval estimate will contain the parameter is expressed as the confidence level.A confidence interval is a specific interval estimate of a parameter determined by sample data and a specific confidence level of the estimate. Let us work out few examples to demonstrate the method of calculating the confidence intervals.
Objective:This section will explain the meaning of the Confidence Interval (CI) in statistical analysis. The CI states that with 92% confidence, the proportion of all similar companies with the plan will between 46% and 56%. Estimates of parameters like mean and proportion which are derived from data collected from samples are often used in statements describing the true parameters of population. Often, statistics are not expressed in terms of one number but rather as a range or an interval with a given level of confidence.

There is a general trade off between the confidence level and the range of the confidence interval. For proportions, the normal distribution approximates the binomial for n x P(hat) is greater than or equal to 5.Most common confidence interval selections are 90%, 95%, or 99% but are dependent on the voice of the customer, your company, project, and other factors. The reliability of a Point estimate as a good estimate is often difficult to find and hence its accuracy is generally questionable, Hence the interval estimates are generally preferred by statisticians over Point estimates.An interval estimate is a range of values to estimate the parameter in question, The interval may or may not contain the parameter. The larger your sample size, the more confidence one can be that their answers represent the population.
Confidence Interval is an Interval estimate for the parameter which also gives the probability of the true parameter falling in that interval. If the sample is not then one cannot rely on the confidence intervals calculated, because you can no longer rely on the measures of central tendency and dispersion.Sampling plans are an important step to ensure the data taken within is reflective and meaningful to represent the population.

Click here for information regarding sampling plans.PercentageThe accuracy of the CI also depends on the percentage of your sample that picks a particular answer. It is easier to be sure of extreme answers than those aren't, thus the interval is not linear.

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