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Tom Reader explains the importance of understanding the difference between fixed and random effects in statistical analysis to avoid pseudo replication. Statistical tests such as t-tests, ANOVA, and regression all use mathematical models to describe how dependent variables are influenced by independent variables. It is crucial to have a working knowledge of basic statistical tests and jargon like factor and dependent variable to correctly analyze data. Fixed effects are caused by independent variables with specific levels, while random effects are influenced by a set of random variables. Understanding these concepts is key to conducting accurate statistical analysis.
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