![]() Please enter your values above, and then hit the calculate button. The following table shows common confidence levels and their corresponding z -values. Your result will appear at the bottom of the page. The z -value, which appears in the margin of error formula, measures the number of standard errors to be added and subtracted in order to achieve your desired confidence level (the percentage confidence you want). Please enter your data into the fields below, with your sample 1 mean being the higher of your two means, select a confidence level (the calculator defaults to 95%), and then hit Calculate. (If you need to calculate means and standard deviations from sets of raw scores, you can do so using our descriptive statistics tools.) The calculation works on the assumption that the two population variances are equal (i.e., it uses a pooled standard deviation in order to calculate the standard error portion of the confidence interval calculation). To perform this calculation you need to know your two sample means, the number of items in your samples, and the standard deviations for your two samples. the confidence interval at 98 confidence level is 3.18 to 3.42. S (M 1 - M 2) = standard error = √(( s 2 p/ n 1) + ( s 2 p/ n 2)) Here we discuss how to calculate Confidence Interval example and a downloadable excel template. What value of z would you use to calculate the 98 confidence interval for the population mean given that you know the population standard deviation. T = t statistic determined by confidence level More precisely, it's actually 1.96 standard errors. If we want to be 95 confident, we need to build a confidence interval that extends about 2 standard errors above and below our estimate. Μ 1 - μ 2 = ( M 1 - M 2) ± t s ( M 1 - M 2) Critical value (z) for a given confidence level. ![]()
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