FAQ: Data Analyses and Conclusions - Causal analysis with observational data

This community-built FAQ covers the " Causal analysis with observational data" exercise from the lesson “Data Analyses and Conclusions”.

Paths and Courses
This exercise can be found in the following Codecademy content:

FAQs on the exercise _ Causal analysis with observational data_

There are currently no frequently asked questions associated with this exercise – that’s where you come in! You can contribute to this section by offering your own questions, answers, or clarifications on this exercise. Ask or answer a question by clicking reply (reply) below.

If you’ve had an “aha” moment about the concepts, formatting, syntax, or anything else with this exercise, consider sharing those insights! Teaching others and answering their questions is one of the best ways to learn and stay sharp.

Join the Discussion. Help a fellow learner on their journey.

Ask or answer a question about this exercise by clicking reply (reply) below!
You can also find further discussion and get answers to your questions over in Language Help.

Agree with a comment or answer? Like (like) to up-vote the contribution!

Need broader help or resources? Head to Language Help and Tips and Resources. If you are wanting feedback or inspiration for a project, check out Projects.

Looking for motivation to keep learning? Join our wider discussions in Community

Learn more about how to use this guide.

Found a bug? Report it online, or post in Bug Reporting

Have a question about your account or billing? Reach out to our customer support team!

None of the above? Find out where to ask other questions here!

> Based on the attached graph, I need to make sure that my answers to questions in the exercise are rational.

Q1: Is margarine consumption correlated with divorce rate?
There is observed correlation between them as both of them tends to decrease starting from 2000 to 2009 where the difference between values along years were almost equal at 2001 and they started to increase with observed saturation from 2002 till 2007 before it returned to decrease again till 2009

Q2: Does consuming less margarine cause fewer people to get divorced in Maine? Why or why not?
It is obvious that low margin consuming results in fewer people to get divorced in Maine, but we aren’t sure if there are any external factors that may contribute in lowering divorce rate


The graph does show correlation between Margarine Consumption and Divorce Rate (in Maine for the years mentioned), so Q1 can be answered in the affirmative i.e. as a yes.

But I don’t think your answer to Q2 is correct. Correlation is not enough to establish causality. You have noticed a correlation, but that by itself is not sufficient to claim that lowering margarine consumption causes the divorce rate to be lowered. Similarly, we can’t claim that lowering the divorce rate causes margarine consumption to be lowered.


Ya you are right for question 2, I missed that

Correlation is not enough to establish causality


I don’t understand how to read this graph. I’ve never seen a graph where there is one variable on the left and also one on the right. Can someone explain? To me it seems we only look at the left side when dealing with the divorce rate and we only look at the right side when viewing the margarine consumed plot.

In this graph, the horizontal axis shows the year, so when you move from left to right you can think of it as time progressing (from 2000 to 2009). The vertical axis shows two different variables, which I think is the confusing part. This is because the two lines (for the two variables, margarine consumed and divorce rate), have two different units. The unit for divorce rate is divorces per 1000, and the variable for margarine consumed is lbs. So in a way, you’re right. If you want to see the actual value of margarine consumed, you’d look at the right side. And if you want to see the number of divorces, you look at the left.

However, to see the trend, you really just need to look at the lines, and how the values change from year to year. The two lines on the graph represent the actual values for the two different variables. The white line represents margarine consumed, and the yellow line represents the divorce rate in Maine, as shown in the legend. This graph is showing that the trends are very similar for the two variables (they are correlated). However, we can’t say just from this info whether there is a causal relationship (that one is directly influencing the other).

Hopefully this helps, happy to answer more questions!


Thank you!!! So, the reason we cannot tell if one causes the other is because there might be another variable or cause that is not displayed?

Or, it looks like married women buy more margarine!


Exactly! The only correlation that I can interpret is that the more married people are, the more margarine consumption is. Even so, I cannot affirm a causality to this variable alone, there would be a lack of more data to associate this fact. And by default, more divorce, less margarine consumption.