| Loadings and Contribution
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Use the options in this group box to generate a histogram and spreadsheet of variable contributions and loading factors.
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| Lineplot (p)
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Click this button to create a line plot of the loading factors for the specified principal component in the
First list (see below). For generating more than one graph, make multiple selections in the
First list. Note that different variables contribute differently to the loading factor of a principal component. The loading factors determine the orientation of the principal components with respect to the original coordinate system. The more influential a variable, the larger its loading factor. Thus, by examining the loading factors, we can tell how different variables contribute to the principal components.
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| Scatter (p)
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Click this button to create a loading factor scatterplot for the principal components selected in the
First and
Second lists. For example, by selecting component 1 in the
First list and component 2 in the
Second, we can create a scatterplot of the p-factors for component 1 against the p-factors for component 2. Scatterplots of the loading factors can be used to examine the relationship between the process variables and the type of influence they exert on the PC model. Clustered variables are positively related to each other and negatively related to those located on the opposite quadrant. Clustered variables also influence the PC model in similar ways.
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 Contribution
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The
Contribution group box contains options for calculating variable contributions to the scores or to the
Hotelling T2 statistic.
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 (Contributions Spreadsheet)
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Click this button to generate the variable contributions in spreadsheet format.
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| Score
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Select this option to generate variable contributions to the score of an observation specified in the Obs. box (see this option description below), in the direction of a principal component selected in the
First list (See this option description below). Different analysis variables make different contributions to the scores.
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| T2
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Select this option to generate variable and time contributions to the Hotelling T2 statistic of the observation specified n the Obs. box
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| Time code
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Use this dropdown list (together with
Batch) to specify an observation for which you want to generate a
Score contributions plot.
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| Batch
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Use this dropdown list to specify a batch for which you want to generate a contributions plot. Use this option together with Time code if generating
Score contribution results.
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| Lineplot (t)
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Click this button to create a line plot of the scores for the principal component selected in the
First list. You can generate more than one graph by making multiple selections in the
First list. The t-scores are the presentation of the original measurements in the new coordinate system. In
TMPCA modeling, the scores are used to examine the normality of a batch. The larger the score of a batch, the less normal the batch is. Deviations from zero with magnitudes comparable or larger than the control limits may indicate abnormalities.
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Click this button to create the same information as above in spreadsheet format.
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| Scatter (t)
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Click this button to create a scores scatterplot for the principal components selected in the
First and
Second lists.
EXAMPLE: Selecting component 1 in the
First list and component 2 in the
Second will create a scatterplot of the t-scores of component 1 against the t-scores of component 2. This graph will also display an ellipse, defined as:
Observations with score values falling outside this ellipse may be outliers. Note that you can generate more than one graph by making multiple selections in the
First and
Second lists. For example, you can generate the scatterplots of components 1 and 2 vs. 3 if you select components 1 and 2 in the
First list and 3 in the
Second. See the
Lineplot (t) option description above for more details
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Click this button to create the same information as above in spreadsheet format.
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| Display text labels
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Select this check box to include variable names or batch identifiers (whichever is appropriate) in the graphs of scores and loading factors (lines and scatter plots).
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| First
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In this list, specify the principal component(s) for which you want to generate scores and loading factor plots and spreadsheets.
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| Second
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In this list, specify the principal component(s) for which you want to generate scores and loading factor plots and spreadsheets.
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| Limits (t)
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Use the options in this group box to define limits for the score plots (line or scatter).
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| Multiply std. dev
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Select this option button to define the upper and lower bounds for the score limits as control standard deviation.
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| Compute from p
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If you select this option button, Statistica will assume that the scores are normally distributed and the 99% confidence levels are used to define the upper and lower limits.
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| Control
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Specify the control limits. When the Multiply std. dev. option button is selected (see above), this value is multiplied by the computed standard deviation for defining the upper and lower limits.
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| Warning
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Select this check box to include an upper and a lower warning limit in the scores graph. Specify the warning limit in the adjacent box. For the Multiply std. dev. option, this value will be multiplied by the standard deviation for the scores to define the lower and upper warning limits.
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