This is the most “famous” Chi-Square statistic.ĥ. The following calculation is made for each condition: Compare the observed and expected frequencies to obtain “reality”. Calculate for each condition the expected frequencies(E) under the assumption that no differences exist among the processes.ģ. Take one subgroup from each of the various processes and determine the Observed frequencies(O) for the various conditions being compared.Ģ. This application of Chi Square is called the Contingency table or row and column analysis.ġ. The ability of inspectors to identify defective parts can be evaluated. Machines may be compared as to their ability to produce precise parts.
It is often necessary to compare proportions representing various process conditions. To test hypothesis of several proportions (contingency table) Ha: The hypothesized distribution is not a good fit of the data.Ho: The hypothesized distribution is a good fit of the data.
The calculation of the Chi square statistic and the determination of its significance is the same as in scenario 1. This can be performed on cross tabulations as well as on frequencies(one-way tabulation). These tests are conducted by calculating the significance of sample deviation from the assumed theoretical(expected) distribution. Chi Square can also be used to determine whether a certain model fits the observed data.
0 kommentar(er)
