Many tests have been developed for this purpose one

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: ge deviation (ppt) in addition to the standard deviation in all experiments. Analysis of Poor Data: Q-test Sometimes a single piece of data is inconsistent with other data. You need a method to determine, or test, if the data in question is so poor that it should be excluded from your calculations. Many tests have been developed for this purpose. One of the most common is what is known as the Q test. To determine if a data should be discarded by this test you first need to calculate the difference of the data in question from the data closest in value (this is called the "gap"). Next, you calculate the magnitude of the total spread of the data by calculating the difference between the data in question and the data furthest away in value (this is called the "range"). You will then calculate the QData, given by gap QData = range and compare the value to that given in the table below. The values in the table below are given for the 90% confidence level. If the QData is greater than...
View Full Document

This note was uploaded on 04/09/2013 for the course CHE CHE 2C taught by Professor Nasiri during the Spring '07 term at UC Davis.

Ask a homework question - tutors are online