A scatter diagram is one of the七个基本质量工具that many professionals struggle with.
散点图也称为散点图,scatter graph, orcorrelation chart.
Other diagrams use lines or bars to display data; a scatter diagram uses dots. This may appear to be a confusing approach at first, but it is often easier than others to understand.
An English scientist, John Fredrick W. Herschel, presented the scatter diagram in 1833 in his study of Orbits of Double Stars.
In 1886, the scatter diagram was popularized by an English Victorian-era polymath named Francis Galton. He is also known as the creator of statistical concepts of correlation.
In this blog post, I will explain the scatter diagram.
Scatter Diagram (Scatter Plot)
通过包括两个变量来绘制散点图。第一个变量是独立的,第二个变量取决于第一个变量。
The scatter diagram is considered the simplest way to study the correlation between these two variables. After determining how they are related, you can predict the behavior of the dependent variable based on the independent variable.
当一个变量可测量而另一个变量不可测量时,散点图很有用。
Definition: According to the PMBOK Guide, a scatter diagram is “a graph that shows the relationship between two variables. Scatter diagrams can show a relationship between elements of a process, environment, or activity on one axis and a quality defect on the other axis.”
Example of Using a Scatter Diagram
You are analyzing accident patterns on a highway. You select the two variables, motor speed and the number of accidents, and draw up the diagram.
画完成后,你注意到number of accidents increases as the speed of vehicles increases. This reveals the correlation between the two.
In most cases, the independent variable is plotted along the horizontal (x-axis), and the dependent variable is plotted on the vertical (y-axis). The independent variable operates as the control parameter because it influences the behavior of the dependent variable.
It is not necessary to have a controlling parameter to draw a scatter diagram. There can also be two independent variables. In that case, you can use any axis for any variable.
Many professionals believe that a scatter diagram is like a鱼骨图因为后者包括两个参数:因果关系。
Note that these two diagrams are different. The fishbone diagram shows you the effect of a cause; however, it does not show the relationship between these two. The scatter plot helps you analyze the correlation between the two variables.
However, the fishbone or Ishikawa diagram can help you draw a scatter diagram. For example, you can use the fishbone diagram to find the two variables (cause and effect) and then use the scatter diagram to analyze their relationship.
Types of Scatter Diagrams
You can classify scatter diagrams in many ways. I will discuss the two most popular based on correlation and slope of the trend. These are the most common in project management.
根据相关性,您可以将散点图分为以下类别:
- Scatter Diagram with No Correlation
- Scatter Diagram with Moderate Correlation
- Scatter Diagram with Strong Correlation
Scatter Diagram with No Correlation
This diagram is known as the “Scatter Diagram with Zero Degree of Correlation.”
Here, the data point spread is so random that you cannot draw a line through them.
因此,您可以得出结论,这些变量不相关。
Scatter Diagram with Moderate Correlation
This plot is known as a “Scatter Diagram with a Low Degree of Correlation.”
Here, the data points are a little closer, and you can see a relationship between these variables.
Scatter Diagram with Strong Correlation
该图被称为“具有高度相关性的散点图”。
在此图中,数据点是接近的,您可以按照其模式来绘制线路。
在这种情况下,您得出的结论是这些变量密切相关。
As discussed earlier, you can categorize the scatter diagram according to the slope, or trend, of the data points:
- 具有强正相关的散点图
- 散布图弱正相关
- 散点图与强相关性很强
- Scatter Diagram with Weak Negative Correlation
- 与最弱(或否)相关性的散点图
强烈的正相关意味着从左到右的可见向上趋势;强大的负相关意味着从左到右的可见下降趋势。弱相关性意味着趋势不太清楚。扁平线是从左到右的最弱相关性,因为它既不是正面也不是负面的。无相关性的散点图表明,自变量不会影响因变量。
具有强正相关的散点图
该图被称为“带正倾斜的散点图”。
在正倾斜中,相关性为正,即,随着x的值增加,y的值将增加。您可以说,沿数据点绘制的直线的斜率将上升。该模式类似于直线。
For example, cold drink sales will increase if the weather gets hotter.
散布图弱正相关
As the value of X increases, the value of Y also increases, but the pattern does not resemble a straight line.
散点图与强相关性很强
该图被称为“具有负倾斜的散点图”。
在负倾斜中,相关性为负,即,随着x值的增加,y的值将下降。沿数据点绘制的直线的斜率将下降。
For example, if the temperature increases, the sale of winter coats goes down.
Scatter Diagram with Weak Negative Correlation
随着x值的增加,y的值将减小,但模式尚不清楚。
Scatter Diagram with No Correlation
There isn’t any relationship between the two variables to be seen. It might be a series of points with no visible trend or a straight, flat row of points. In either case, the independent variable does not affect the second variable; it is not dependent.
散点图的局限性
- Scatter diagrams cannot give you the exact extent of potential correlation.
- A scatter diagram does not show a quantitative measurement of the relationship between the variables. It only shows the quantitative expression of quantitative change.
- This chart does not show you the relationship for more than two variables.
Benefits of a Scatter Diagram
- It shows the relationship between two variables.
- It is the best method to map out a non-linear pattern.
- The range of data flow, like the maximum and minimum values, can be determined.
- Patterns are easy to observe.
- Plotting the diagram is simple.
When You Should Use a Scatter Diagram
You should use the scatter diagram in the following cases:
- If two variables pair well together, you can draw a scatter plot to see their relation and correlation. For example, working hours versus earnings.
- To figure out if two variables share a relation. For example, if there is any relation between the temperature rise with the equipment malfunctioning.
Points to Remember While Plotting Scatter Diagram
- It is not always guaranteed that two variables share a relationship if the chart shows a correlation. It can be a coincidence or caused by a third variable.
- You can plot the scatter diagram when you have a large amount of data.
- The more the data resemble a straight line, the stronger the correlation.
- Data coverage should be wide for plotting a scatter chart.
Summary
Scatter diagrams are useful in determining the relationship between two variables. This relationship can be between two causes or a cause and an effect. It can be positive, negative, or not correlated at all.
第一个变量是独立的,第二个变量取决于第一个变量。To analyze the pattern of the relationship, you change the independent variable and monitor the changes in the dependent one. A scatter diagram can have two independent variables.
A scatter diagram is an important concept from a PMP exam point of view. Please understand it well.
Why is it difficult to use qualitative attributes in a scatter plot?
我们的教授问使用散点图来查看the relation for example the total development cost and the annual produce but the data will plot is only one from each so how can we see the relation. I hope you can help us.
Thanks Fahad
You are welcome Ali.
散点图可以具有两个自变量(根据上述摘要) - 这是如何可能的?它应该具有一个自变量和一个因变量知道吗?
In some cases, a scatter diagram can have two independent variables.
This helps me a lot
I am a Geography student and those examples and that limitations and benefits helps me a lot, thanks…
You are welcome Rahul.
Good morning.. Plz say in which book you taken this for reference. I need urgent to claim answer for competitive exams
PMP reference books and internet search.
To much helpful artical and in a very esay language tha would b understandable.
Thanks Imran for your visit.
Well done. Clear and concise with everything needed for a beginner to understand the Scatter Diagram.
谢谢Stephen的评论。
Thanks for this information; very clear and precise.
感谢Brian的评论并参观。
惊人的。谢谢法哈德。
You are welcome Khalilullah.
thanks a lot
欢迎您Junaid。
Easy to understand
感谢拉胡尔。
Excellent.
A bit off the topic… I’ve been wondering if there are many opportunities as a project manager , for someone who has been in steel fabrication and welding as their base career? Sorry. I hope this makes sense. Thanks
Thank u so much helped a lot
You are welcome Senumi.
NICE SIR IT IS GREAT ….PLZ SHOW ONE EXAMPLE WITH DATA
Hello Randiv, when I will update the post, I will try to add some chart with data.
what is correlation chart
这是散点图的另一个名称。
不错的艺术
Thanks Pramod.
问候法哈德,
尼斯(Nice)和主题为PM有抱负者(PM Asportant),我也想增加几行。
A scattered diagram is a correlation and they may be positive or negative and are represented by a regression line and are generally used when QC finds variable and that might not be in control and systematic and changing in one another variable.
Independent variable is plotted along the horizontal line axis whereas dependent variable is plotted along the vertical axis.
Thanks & Best Regards
https://tiemchart.com/
Thanks Almesh for sharing your thoughts.
could u pls ……post some solved question related to scatter diagram?
您好Humna,这次我忙于其他活动,因此无法满足您的要求。我建议您参考任何出色的PMP考试参考书,以查找本文的问题。
very informative ….thank u so much
You are welcome Humna.
good work
Thanks Joran.
Why 2 points lie one on top of other?
散点图由数百个图组成,其中一些图可能位于其他图的顶部。您必须看到模式。
The scatter diagram graphs pairs of numerical data, with one variable on each axis, to look for a relationship between them. If the variables are correlated, the points will fall along a line or curve. The better the correlation, the tighter the points will hug the line.
Thank you it was usefull for me .
You are welcome Hermenegildo.
谢谢你最好吗?
感谢Arshley的评论。
非常感谢很好的解释。
May you please explain “Decision tree”?
再次感谢
Sure, soon I will write a blog post on it.
风险评估:在这里,您可以评估当前风险,如果它们仍然有效或可能过时,则可以关闭。
风险Audit: It deals with effectiveness of risk responses as well as the effectiveness of the risk management process.
Hi
please could you explain what are diffrents between risk audit and risk assessment in control risk .
Thank you
非常感谢你。如此有用
不客气迈克。
Thanks Fahad. I have been going through all your posts and they are indeed very helpful.
Please keep helping PMP Aspirants like me with your blogs.
Thanks once again!!!
You are welcome Ritika.
I’ve really enjoyed the explanation you made above. Thank you
You are welcome Bilshan.
I didnt understand the exact diff b/w two types of scatter diagrams: type of correlation ans slope of trend coz both the types are showing the same thing. Pls throw some light on my confusion.
注意点的传播。它显示了它们的关系程度。
非常好的文章先生
不客气。
Very good article and very clear explanation. Really appreciate the effort.
Thanks Raj.
asalaam-o-alaikum!
The way you explain every topic is marvelous. Thank you.
Could you please explain Resource optimization techniques and Influence diagram.
Okay.
I have noted it, and soon you will see a post on this topic.
Thanks for the good article.
pls note that there’s one typo, it should be “dependent” variable is plotted on the vertical axis (y-axis).
“Usually independent variable is plotted along the horizontal axis (x-axis) and independent variable is plotted on the vertical axis (y-axis) “
感谢您的评论Vijay。
错误已纠正。
Good article. Thanks a lot.
You are welcome Bijoy.
thank you.. Really i am understood very well .Mnay thanks for you.
You are welcome Muhsin.
第一个变量是独立的,第二个变量取决于第一个变量
Correct.
thank you so much.Super
You are welcome Sundarishanmugam.