This page shows how elements of a systems can be eliminated as causes in problem troubleshooting. The principles of twenty questions are frequently used in the business world to conduct computerized searches of massive data bases. These are called a binary searches and are one of the fastest search methods available. To conduct binary searches, data must be sorted in order or alphabetized. The computer determines which half of the list contains the item. The half containing the item is divided in half again and the process repeated until the item is found or the list can no longer be divided. Problem solvers should avoid focusing on the cause and instead ask which elements of the system can be eliminated as causes.

Date Of Record Creation | 2005-05-23 14:03:00 |
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Date Last Modified | 2005-05-23 14:03:00 |

Date Of Record Release | 2005-05-23 14:03:00 |

Alternate Title | Excellence in Curriculum Intigration through Teaching Epidemiology |

Source | http://www.graphpad.com/quickcalcs/ |

Relation | Centers for Disease Control and Prevention |

Email Address | intuitor@intuitor.com |

Date Issued | 2004 |

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Typical Learning Time | 1-2 hours |

Author Name | Intuitor.com |

Author Organization | Intuitor.com |

General Comments | Dead Link |

Technical Requirements | Java installed |

Comments | The trial analogy is good for definining and differentiating between Type I and Type II errors; however, the analogy becomes awkward and labored as it continues to be used to define and illustrate the probabilities of these errors. It is probably better to switch to an actual statistical hypothesis test (a familiar one from a homework assignment) to explain and illustrate alpha and beta. |

Content Quality (Concerns) | 1. The text description here sometimes discusses an error and the probability of an error interchangably. These are distinct concepts, and the instructor needs to help students understand this. 2. The authors incorrectly state that alpha is "equal to the p-value." Most statisticians would agree that alpha is the significance level. 3. The authors don't make it explicit that alpha and beta are inversely related only if the amount of information is assumed constant. In fact, if more information is gathered, then it is possible to reduce both probabilities because the relevant sampling distributions become less variable. 4. The false notion that researchers always want to evaluate the alternative hypothesis is perpetuated. 5. In this applet only greater than alternatives are allowed. The instructor should be sure to explain to students that other alternatives are available. |

Content Quality (Strengths) | The text illustration of this item is nicely written and fun to read. It uses an easily understood analogy of a criminal trial. Additionally, the applet is very helpful for understanding the relationship between Type I and Type II errors. This is done by allowing the user to move the location of the true distribution relative to the distribution under the null hypothesis. |

Ease of Use (Concerns) | None. |

Ease of Use (Strengths) | Very easy to use. The applet layout is uncluttered and intuitive (no pun with the URL intended). |

Potential Effectiveness (Concerns) | The text explanation is quite similar to a textbook explanation. The included applet will need specific questions for the student to help them explore the relationship. The instructor may also want to supplement this applet with connections to real world examples other than the trial analogy. |

Potential Effectiveness (Strengths) | The applet is useful for visually and dynamically illustrating the connection between alpha and beta when the amount of information is held constant. The applet could be helpful if a series of guided questions were written to accompany this material, or if the instructor used it in class where he/she could ask the questions and explain. |

Content Quality (Rating) | 4 |

Ease of Use (Rating) | 5 |

Potential Effectiveness (Rating) | 4 |

Source Code Available | 1 |

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