What is the difference between males and females likely to be in the population? That, of course, is the difference in the sample. The sample estimate, based on 1698 respondents, is that males, on average, earn $5299 more than females ($44,640 – $39,341). How much better do males do than females in the income stakes? The figures in Table 1 below were obtained for the average income of males and females in a fictitious survey for unemployment. How to Interpret Confidence Intervals for Means However, in cases where such precision is not required there is a point where the gain in precision is not worth the cost of increasing the size of the sample. Very precise population estimates with little margin for error require large sample sizes and/or resampling techniques like bootstrapping. As a general guide, to halve the standard error the sample size must be quadrupled. One thing we can do is to increase the sample size. Usually there is little that we can do about changing variation in the population. The size of the standard error is due to two elements: Sampling error is measured by the standard error statistic. If we assume the confidence level is fixed, the only way to obtain more precise population estimates is to minimize sampling error. The greater the confidence level, the wider the confidence interval. The width of the confidence interval is a function of two elements: What Determines the Width of the Confidence Interval?Ī narrow confidence interval enables more precise population estimates. Confidence intervals can be used in univariate, bivariate and multivariate analyses and meta-analytic studies. One way of shedding more light on those issues is to use confidence intervals. Significance tests on their own do not provide much light about the nature or magnitude of any effect to which they apply. One issue with using tests of significance is that black and white cut-off points such as 5 percent or 1 percent may be difficult to justify.

Sample confidence interval analysis