In project management, you may need to see repeated regular behaviors of things or you may want to see the direction that something is changing and use them to determine the amount of effort and resources that need to be allocated to ensure successful outcomes.
Scatter Diagrams are really great types of plots that we can use to help see relationships in our data. To be a little bit more specific, in a scatter plot, we use these to show a relationship between two variables. Now, usually, a dot is used to show an individual pair of data. Let's look at some other terms that are also used when describing these scatter plots.
Example
We'll take the data and represent both of our variables along both of these axes. Here on the bottom one, we call this our x-axis. This is where we'll display our independent variable. Along the other line, our y-axis, we'll display the second variable. We'll call this our dependent variable. Now, you might be curious, like how on earth do we know which one's the dependent variable? How do we know which one is the independent variable? Well, think of it this way: the dependent variable will change as a result of what the independent variable is doing. And when we get to my example, you'll probably be able to more clearly see which one is depending on the other one's value.
Alright, let's give it a try. So, we want to create a scatter plot for the following data in this chart or table here, which represents the hours of studying and a particular exam score that some students had. So, which one of these would depend on the other one? Well, we would think that whatever exam score they got probably depended on the hours of studying. So, we will say that the hours of study are independent and the exam scores are dependent.
Now, it's also important to mark out a scale so we can put all of these data values in here. And looking at the hours of study, it looks like somewhere between zero and ten hours is probably good. So, let's mark off ten tick marks. Along the other side, this is where our exam scores will go. Let's just do zero to 100.
Now, the way this works is we want to put a data point at the intersection of hours and scores so that one point represents a pair of data. Let's start off with the first one. So, we want to put two hours of studying and a score of 53. So, we'll first find the hours of studying, there's our two, and we'll put a dot where it intersects 53. So, just a little bit above the value of 53.
Let's do this again. So, we got four and a half for 35. So, four and a half halfway between up to ten, twenty, thirty and a half. Not bad. Okay, up to five. Five needs to go all the way up to 91. So, way up here. Let's keep going. We also have five, which is at 72. Let's see, so 50, 60, 70...
Notice how we get two values for both four and five, and that's okay. Sometimes that can happen with these scatter plots. Let's see, six. We need a dot at 63. We need one at 62. Let's see, ten over here. We need one at 85. Fifty, sixty, seventy, eighty, halfway, 85. Let's see, nine and a half, so halfway between these two. This one's going up to 78. Fifty, sixty, seventy, almost 80 but not quite.
Let's see, one more. Eight. Ah, there, almost got a perfect score, 99, way near the top.
The advantage of having something like a scatter plot to see all of your data points is you can start to see if there are possibly relationships among these two different variables. And you know if I was looking at this and if it was real data, you know, I might expect that maybe exam scores are, you know, really have a strong relationship with the hours of studying. Maybe the more we study, the higher our scores are.
Now, if this is our data, then, you know, actually looking at maybe I'm not convinced that these two things are really related because, you know, the people who are studying a lot aren't really scoring a whole lot better than some people who only score a little bit. They're still actually scoring pretty good. But it's a nice visual way that we can see those relationships and get a sense of what is happening between those two variables.
When to Use?
It is recommended to be used especially when you need to find some peculiar points in the data that you have obtained. These types of data potentially compromise the results of the analysis. Scatter diagrams are useful here. Being able to recognize any unusual data points is essential to guarantee that the data is accurate and trustworthy.
Graphically illustrating data through scatter diagrams allows project managers to detect patterns and trends more quickly and easily than simply viewing the data in tabular form. This type of visualization simplifies complicated data, allowing a deeper comprehension of the information.
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