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Industrial Statistics with Minitab by Xavier Tort-Martorell Llabres, Lluis Marco Almagro, Pere Grima Cintas

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6.4 Humidity

During one week, daily measures of the content of humidity of 20 packages of a certain product were taken. These packages were chosen randomly at the end of the packaging process. The corresponding data is contained in the file HUMIDITY.MTW. What conclusions can be drawn from the graphical analyses of these data?

There are several options to analyze these data graphically. An appropriate graph to represent the weekly evolution of the humidity is a time series plot. To construct it, the data must first be stacked in a single column.

Rarely is the available data already arranged in a convenient way for the analysis.

To pile up the data, proceed as usual: Data > Stack > Columns

nc06uf020.eps

Time series diagram of the variable ‘Week’.

Graph > Time Series Plot: Simple. Series: Week

nc06uf021.eps

The shown process is not stable: there is first an increasing trend followed by a sudden jump downwards. To distinguish the weekdays, different line types and colors can be used. To do so, double-click on the line. A dialog box that allows you to edit the lines appears:

nc06uf022.eps

Notice that, by ...

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