# Data Analysis week 5

rename
winniesmith2's
version from
2017-10-30 10:48

## Section

Question | Answer |
---|---|

What are type 1 errors | alpha error. This is the error level we set when testing the null hypothesis |

What happens if you choose a sample that is too small? | -Inconclusive results – type 2 errors -Calculations cannot be completed e.g. ,some tests require a certain n -Sample may be unrepresentative |

what are type 2 errors | false negatives |

What happens if a sample size is too large? | -Collecting more data than is necessary is costly in many ways -You have the statistical power to pick up smaller and smaller differences and label them as ‘significant’ . Does the difference matter? may be statistically different but is this biological/clinically significant. |

An appropriate sample size depends on what | -The size of the effect that we think is interesting -The alpha level -The variability we expect to find in our sample |

examples | page 7 onwards |

What is an appropriate sample size? | To estimate this we need to know an estimate of the variability we expect in our sample |

How to calculate a sample size | Specify a sample size to detect a pre-defined level of difference in a statistical test (example used here is t-test). -page 13. EQUATIONS. |

what does LSD mean | lowest significant difference. |

some considerations for working out sample size | The difference you want to detect will be based on your knowledge of the variables you are testing from past research. Information on the likely standard deviation needs to come from previous studies. If these do not exist you need to do a pilot study first to gain this information. (these calculations only consider alpha, beta beyond scope of module). |

examples | use power point |

What would you do for a one tailed test | change the critical value to reflect a one tailed test . this would reduce the required sample size. |

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