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Statistics

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."

Details

Degrees

Biological science
Biomedical science
Forensic science
Foundation science
Pharmaceutical science

Discipline

Scientific literacy

Topic

Statistics

Purchase option

The Smart Worksheet Library

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Biological science
Biomedical science
Forensic science
Foundation science
Pharmaceutical science
hypothesis testing
statistics
Scientific literacy
The Smart Worksheet Library
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