Search results
Results from the WOW.Com Content Network
The corresponding conditional of a valid argument is a logical truth and the negation of its corresponding conditional is a contradiction. The conclusion is a necessary consequence of its premises. An argument that is not valid is said to be "invalid". An example of a valid (and sound) argument is given by the following well-known syllogism:
Of the many and varied argument forms that can possibly be constructed, only very few are valid argument forms. In order to evaluate these forms, statements are put into logical form . Logical form replaces any sentences or ideas with letters to remove any bias from content and allow one to evaluate the argument without any bias due to its ...
Statistical conclusion validity is the degree to which conclusions about the relationship among variables based on the data are correct or 'reasonable'. This began as being solely about whether the statistical conclusion about the relationship of the variables was correct, but now there is a movement towards moving to 'reasonable' conclusions ...
When a valid argument is used to derive a false conclusion from a false premise, the inference is valid because it follows the form of a correct inference. A valid argument can also be used to derive a true conclusion from a false premise: All tall people are musicians. (Valid, False) John Lennon was tall. (Valid, True)
Statistical conclusion validity is the degree to which conclusions about the relationship among variables based on the data are correct or "reasonable". This began as being solely about whether the statistical conclusion about the relationship of the variables was correct, but now there is a movement towards moving to "reasonable" conclusions that use: quantitative, statistical, and ...
The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present.
For premium support please call: 800-290-4726 more ways to reach us
One approach that is commonly used is to have the model builders determine validity of the model through a series of tests. [3] Naylor and Finger [1967] formulated a three-step approach to model validation that has been widely followed: [1] Step 1. Build a model that has high face validity. Step 2. Validate model assumptions. Step 3.