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Chapter 9: Comparing the means of one and two samples of normally distributed data

Chapter 9: Comparing the means of one and two samples of normally distributed data

pp. 108-129

Authors

, Central Queensland University
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Summary

Introduction

This chapter explains how some parametric tests for comparing the means of one and two samples actually work. The first test is for comparing a single sample mean to a known population mean. The second is for comparing a single sample mean to an hypothesised value. These are followed by a test for comparing two related samples and a test for two independent samples.

The 95% confidence interval and 95% confidence limits

In Chapter 8 it was described how 95% of the means of samples of a particular size, n, taken from a population with a known mean, μ, and standard deviation, σ, would be expected to occur within the range of μ ± 1.96 × SEM. This range is called the 95% confidence interval, and the actual numbers that show the limits of that range (μ ± 1.96 × SEM) are called the 95% confidence limits.

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