And then you'll find the Probability Plot over here, select. For the probability plots, we go to Graph. But you can have the rest there too, it doesn't matter. I only copied the variable THT or the total handling time into Minitab. So, pause the video, load your data before you continue. Let's take a look at how to make one with Minitab. But is it then Weibull or lognormally distributed? The tool we will use to find the best fitting distribution is called the probability plot. From the shape of the histogram, we can already see that the data is not normally distributed. Let's return to our example of the total handling time. You will see the normal, the Weibull, or the lognormal distribution. In the Six Sigma project, you will often only encounter these three though, so that makes your life a lot easier. There are many different probability distributions. You saw them already in the video on normal, Weibull, and lognormal distributions. But first, let me show you the distributions that we will consider. In this video, I will show you how to fit a distribution to this data. And you gathered data about this process, and one of the variables is the total handling time. The CTQ is therefore Total Handling Time. Which is the total time that employee is busy with answering a call. For that, we first go back to our call center, where a project has started to improve the total handling time. So, let's have a look at a probability plot. Well, you will need that information for many statistical tools, such as the empirical CDF, ANOVA or regression, which are all coming up in the next videos. But why do you want to know which distribution fits to your data. We will study a tool called the probability plot to find the correct distribution for your data. But how do you know that your data follows this distribution? If this is the histogram of your CDQ, does it follow the normal distribution? In this video, I will teach you how to answer this question. Ever heard of the normal distribution? And did you know that it looks like this? You probably have.
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