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17.1.12 Dixon's Q-Test

Q-Test.png

Supporting Information

To open the Dixon's Q-test dialog box from the menu:

  1. Click Statistics: Descriptive Statistics: Dixon's Q-test (Open Dialog...)


See Also:

Dialog Box Controls

Results Log Output

Select to output results to the Results Log.

Recalculate

Controls recalculation of analysis results:

  • None
  • Auto
  • Manual

For more information, see: Recalculating Analysis Results

Input

Number of (replicate) observations must be between 3 and 10 (inclusive) and contained in one column.

For help with range controls, see: Specifying Your Input Data

Significance Level

Option list:

  • 0.1
  • 0.05
  • 0.01
Outlier Plot

Select to generate an outlier plot. Scatter plot with upper and lower confidence limits and dataset mean as line plots.

Q-Test Plot Data

Worksheet range to output the outlier plot data (available if Outlier Plot is selected).

For help with the range controls, see: Output Results

Grubbs Report

The worksheet range to output the report table.

Algorithm

For a series of results from repeated measurements:

  1. Rank n results in ascending order, assigning them values of x_{1} to x_{n}.
  2. Calculate the test statistic Q, as:
    Q=\frac{ x_{2}-x_{1} }{x_{n}-x_{1} } (for testing if smallest observation is an outlier),
    or
    Q=\frac{ x_{n}-x_{n-1} }{x_{n}-x_{1} } (for testing if highest observation is an outlier).
  3. Compare the calculated Q value with Qcritical (critical value is obtained from a table of Q values, using sample size  n and significance level).


Handling Missing Values

The missing values in the data range will be excluded in the analysis

References

Stephen L R. Ellison, Vicki J. Barwick and Trevor J Duguid. Farrant. 2009. Practical Statistics for the Analytical Scientist. The Royal Society of Chemistry, Cambridge, UK.

 

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