Trimmed Mean Because the mean is very sensitive to extreme values, we say that it is not a resistant measure of center. By deleting some low values and high values, the trimmed mean is more resistant. To find the 10% trimmed mean for a data set, first arrange the data in order, then delete the bottom 10% of the values and delete the top 10% of the values, and then calculate the mean of the remaining values. Refer to the BMI values for females in Data Set 1 in Appendix B, and change the highest value from 47.24 to 472.4, so the value of 472.4 is an outlier. Find (a) the mean; (b) the 10% trimmed mean; (c) the 20% trimmed mean. How do the results compare?

Answer:

Step 1 of 3</p>

BMI |

22.13 |

27.2 |

29.21 |

35.4 |

26.79 |

20.85 |

25.68 |

36.38 |

18.71 |

19.43 |

47.24 |

24.91 |

26.6 |

33.11 |

28.65 |

24.96 |

20.31 |

41.28 |

20.85 |

26.21 |

17.62 |

37.48 |

26.36 |

44.6 |

23.7 |

24.22 |

33.68 |

20.37 |

26.41 |

29.02 |

31.21 |

29.18 |

25.89 |

23.5 |

39.98 |

24.8 |

27.2 |

42.77 |

31.3 |

22.44 |

(a) The "Mean" is computed by adding all of the numbers in the data together and dividing by the number elements contained in the data set.

Mean = = 28.4407