Confidence analysis

By Saul McLeod , published June 10, As the sample size increases, the range of interval values will narrow, meaning that you know that mean with much more accuracy compared with a smaller sample. We can visualize this using a normal distribution see the below graph. For example, the probability of the population mean value being between
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Confidence Intervals

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What are confidence intervals? | Simply Psychology

Say you were interested in the mean weight of year-old girls living in the United States. Since it would have been impractical to weigh all the year-old girls in the United States, you took a sample of 16 and found that the mean weight was 90 pounds. This sample mean of 90 is a point estimate of the population mean. A point estimate by itself is of limited usefulness because it does not reveal the uncertainty associated with the estimate; you do not have a good sense of how far this sample mean may be from the population mean. For example, can you be confident that the population mean is within 5 pounds of 90?
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Introduction

As noted in earlier modules a key goal in applied biostatistics is to make inferences about unknown population parameters based on sample statistics. There are two broad areas of statistical inference, estimation and hypothesis testing. Estimation is the process of determining a likely value for a population parameter e. In practice, we select a sample from the target population and use sample statistics e. The sample should be representative of the population, with participants selected at random from the population.
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In statistics , a confidence interval CI is a type of estimate computed from the statistics of the observed data. This proposes a range of plausible values for an unknown parameter for example, the mean. The interval has an associated confidence level that the true parameter is in the proposed range.
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