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Introduction
Martin van Rongen, Matt Castle, Emer Jones, Rob Nicholls, Holly Pavey, Vicki Hodgson
today

Welcome to Core statistics!

These sessions are intended to enable you to perform core data analysis techniques appropriately and confidently using R or Python.

  • 6 lecture-practicals
  • Ongoing formative assessment exercises
  • No formal assessment
  • No mathematical derivations
  • No pen and paper calculations

They are not a "how to mindlessly use a stats program" course!

Core aims {.unnumbered}

There are several things that we try to achieve during this course.

::: callout-note

Course aims {.unnumbered}

To know what to do when presented with an arbitrary data set e.g.

  1. Know what data analysis techniques are available
  2. Know which ones are allowable
  3. Be able to carry these out and understand the results :::

Core topics {.unnumbered}

  1. Simple hypothesis testing
  2. Categorical predictors
  3. Continuous predictors
  4. Two predictors
  5. Multiple predictors
  6. Power analysis

Practicals {.unnumbered}

Each practical document is divided up into various sections. In each section there will be some explanatory text which should help you to understand what is going on and what you're trying to achieve.