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Lesson 4: Inferential Statistics and Regression Modeling
2 Inferential Statistics < Back | Next >
Inferential statistics are used to draw inferences about a population from a sample.
Example

For instance consider an experiment where tree growth rates were increased by 25 percent following a forest thinning operation on 10 sites compared to tree growth rates on 10 sites which were not thinned. Inferential statistics allows us to decide if the increased growth rates are due to chance or are real.

There are primarily two ways to use inferential statistics:

  1. The first is to estimate a parameter about a population.
  2. The second is to test a hypothesis.

For the example above, the hypothesis would be forest thinning has no effect on tree growth rates. This type of hypothesis is often called the null hypothesis, and is the first step in conducting a hypothesis test. Another way we could use inferential statistics is to simply predict or estimate what the average effect of the thinning was on tree growth.

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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