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Statistical tests

t-test fundamentals

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Delve into t-test fundamentals for hypothesis testing through varied scenarios in biomedical science, pharmacology, nutrition, and microbiology. Develop skills in defining hypotheses, validating data assumptions, selecting appropriate t-tests, calculating the t-statistic and degrees of freedom, and interpreting results using the p-value.

Learning outcomes

  • Define null and alternative hypotheses in the context of t-tests.
  • Define the assumptions of t-tests (e.g., normality, homogeneity of variance) and their implications.
  • Identify the appropriate t-test based on sample type and the choice between one-tailed or two-tailed analysis.
  • Calculate the t-statistic and degrees of freedom, and find the critical value for a t-test.
  • Interpret the results of a t-test based on the p-value.
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Skills

Manipulating and Presenting Data

  • How to identify the appropriate type of t-test
  • How to calculate the t statistic and degrees of freedom
  • How to obtainin the critical value from t-distribution tables

Interpreting and Analysing Data

  • How to define hypotheses
  • How to assess whether example data meets the normality and equal variances assumptions
  • How to draw conclusions about t-tests results based on the p-value

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Details

Degrees

Biomedical science
Biological science
Forensic science
Foundation science

Modules

Scientific literacy

Topic

Statistical tests

Purchase option

The Smart Worksheet Library

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