Title: Confidence intervals for the Scottish Health Survey - gov.scot
Headings: Confidence intervals for the Scottish Health Survey
Confidence intervals for the Scottish Health Survey
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What is a confidence interval?
Why do we need confidence intervals?
What is a confidence level?
Can we reduce the width of our confidence interval to increase precision ?
What impact does sample size have on confidence intervals?
When should confidence intervals be used?
How to use confidence intervals to estimate change
How does a complex survey design affect confidence intervals?
How to report confidence intervals?
How to present confidence intervals in Excel
Useful links:
Representing confidence intervals in Excel
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Content: change from 99% to 95%) or reduce the standard deviation. See below for more details on sample size and confidence intervals. What impact does sample size have on confidence intervals? It is important to recognise that it is our sample size that influences the margin of error (ie the confidence interval). The true size of the population does not affect it. Confidence intervals from large sample sizes tend to be quite narrow in width, resulting in more precise estimates, whereas confidence intervals from small sample sizes tend to be wide, producing less precise results. However, after reaching a certain sample size it is not really worth increasing our sample size any further. Increasing the sample size from 100 to 500 reduces the confidence intervals from 9.8 to 4.3, whereas increasing the sample size further to 1000 only reduces the confidence intervals to 3.1. A more detailed discussion on the impact of sample size on confidence intervals is available. Sample sizes for many Government surveys need to be large to allow a minimum sample size for analysis of the smaller sub-groups eg Health Boards and other sub-groups of interest: