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In the third Minitab tutorial we will accompany the quality improvement project of Smartboard Company, to analyze the scrap rate of the last fiscal year’s by using a boxplot analysis. In this Minitab tutorial, we will understand how the team compares different data groups to find out for example, whether more or less scrap was generated on certain production days, than on the other production days. In this context, we will learn what a boxplot is, how it is structured in principle, and what useful information this tool provides. In this Minitab tutorial, we will also discover that the particular advantage of a boxplot analysis is, that this graphical form of presentation allows us to compare statistical parameters such as median, arithmetic mean values, and minimum and maximum values of different data sets, in a compact and clear way. We will also learn how to include additional information elements into the data display, carry out a hypothesis test for data outliers, and create and interpret a single value diagram. The automation of recurring analyses by using of so-called macros, which is particularly useful in day-to-day business will also be introduced. Finally, we will create a personalized button in the menu bar, to perform recurring daily analysis routines – for example for the daily quality report – with a simple click in order to save time in the turbulent day-to-day business.


  • Boxplot analysis, fundamentals
  • Basic structure and interpretation of boxplots
  • Quantiles, quartiles, medians and arithmetic means in boxplots
  • Display of data outliers in the boxplot
  • Boxplots for an even data set
  • Boxplots for an odd data set
  • Boxplot types in comparison
  • Create and interpret boxplot
  • Working in boxplot editing mode
  • Hypothesis test for outliers according to Grubbs
  • Generating and interpreting single value charts
  • Automation of analyses with the help of macros
  • Creating an individual button in the menu bar