Statistical tests

ANOVA analysis

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Investigate how sample variability is used to compare more than two groups through various scenarios in biomedical science. Develop skills in defining hypotheses, validating data assumptions, interpreting the F-statistic and p-values, and reviewing the output of statistical tests to make conclusions about the results.

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Learning outcomes

Identify features of how data is assessed with the one-way ANOVA.
Define null and alternative hypotheses in the context of the one-way ANOVA.
Define the assumptions of the one-way ANOVA (e.g., normality, homogeneity of variance, data relationships).
Interpret the results of a one-way ANOVA based on the F-statistic and the critical value for a one-way ANOVA.

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Skills

Concepts, Principles and Theories

Identify the factor being investigated in a study
Identify the limitations of the results of a one-way ANOVA

Interpreting and Analysing Data

Examine the features of a one-way ANOVA
Distinguish whether the group data are independent
Assess whether example data sets have a normal distribution
Compare variance in different data sets
Interpret the output of tests and draw conclusions based on the results of ANOVA and further tests

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Student

University of Glasgow

“It’s just at that point where it is not telling you the answer but it’s helping you get there."

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Degrees

Biological science

Biomedical science

Forensic science

Pharmaceutical science

Foundation science

Modules

Scientific literacy

Topic

Statistical tests

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The Smart Worksheet Library

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