Chapter 5: Analysing the Data |

## Confidence intervalsInterval estimation is used when we wish to be fairly certain that the true population value is contained within that interval. When we attach a probability statement to an estimated interval, we obtain a confidence interval. Confidence is defined as 1 -
(1 minus the significance level). Thus, when we construct a 95% confidence interval, we are saying that we are 95% certain that the true population mean is covered by the interval - consequently, of course, we have a 5% chance of being wrong. Any statistic that can be evaluated in a test of significance ("hypothesis testing") can be used in constructing a confidence interval. Always, when constructing a confidence interval, two limits, "Upper" and "Lower", are computed. For each limit, the information needed is the computed statistic The upper and lower boundaries for the confidence interval for the t-statistic given above are: Lower Limit = - t / Upper Limit = + t / In Psychology we are not often concerned with estimating the actual value of a population parameter, hence confidence intervals are not very common. Actual values are more common in agriculture say where you want to establish, with a certain degree of confidence, whether 6 bags to the hectare are needed, or 10.7 grams of protein per day, or, in public surveys and opinion polls. where findings are often reported as say: "46% ± 2% are in favour of the government". In research psychology we are mostly concerned with whether two groups are |

© Copyright 2000 University of New England, Armidale, NSW, 2351. All rights reserved Maintained by Dr Ian Price |