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Lesson 4: Inferential Statistics and Regression Modeling
8 ANOVA or Analysis of Variance < Back | Next >
So far we have discussed comparing the means of two populations to each other and comparing the population mean to another number. However, we often want to compare many populations to each other.
Example

We may want to compare regeneration rates for three different tree species in northern Idaho. We would begin by taking samples from each population and then calculate the means from the three samples and make an inference about the population means from this.

It is common since that these three mean regeneration rates would all be different numbers however, this does not mean that there is a difference between the population means for the three tree types.

To answer that question we can use a statistical test called an analysis of variance or ANOVA. This test is widely used in natural resources, and you are bound to come across it when reading scientific literature.

The use of an ANOVA implies the following:

  1. all the populations are normally distributed (follow a bell shaped curve)
  2. all the population variances are equal,
  3. and all the samples were taken independently of each other and are randomly collected from their population

Generally, our null hypothesis when conducting an ANOVA is that all the population means are equal and our research hypothesis will be that at least one of the population means is not equal.

Although an ANOVA is widely used and it does indicate that a population mean is different than others, it does not tell us which one is different from the others.

Additional Information

Conducting an Analysis of Variance

LESSON 4
1 Overview
2 Inferential Statistics
3 Predicting Population
4 Using a confidence interval
5 Hypothesis Testing
6 One and Two Tailed Tests
7 Comparing the Means
8 ANOVA or Analysis of Variance
9 Multiple Comparison Procedures
10 Regression Models & Correlation
< Back | Next >

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