PROBLEM 1 -Does correlation necessarily imply causation? What are the differences between causation and correlations? Do you have any examples?

"Correlation is not causation" is a statistics mantra. It is drilled, military school-style, into every budding statistician. But what does it actually mean? Well, correlation is a measure of how closely related two things are. Think of it as a number describing the relative change in one thing when there is a change in the other, with 1 being a strong positive relationship between two sets of numbers, -1 being a strong negative relationship, and 0 being no relationship whatsoever.

"Correlation is not causation" means that just because two things correlate does not necessarily mean that one causes the other. As a seasonal example, just because people in the UK tend to spend more in the shops when it's cold and less when it's hot doesn't mean cold weather causes frenzied high-street spending. A more plausible explanation would be that cold weather tends to coincide with Christmas and New Year sales.

-HTTPS://www.theguardian.com/science/blog/2012/jan/06/correlation-causationLinks to an external site.

Have you ever observed similar examples? If you type correlation vs. causation in google, you will find many articles and video content on this topic, full of compelling examples. Distinguishing the difference between correlation and causation is crucial in today's world, where we are constantly being presented with data and charts. So many times, the data/charts suggest a correlation, but it is being interpreted as causation.

You can find an article about this topic in the business decision-making domain in the reference section.Make sure you read it.

In your response, please define causation and correlation separately. And talk about the case correlation is not due to causation. Do you have any examples?

:https://hbr.org/2021/11/leaders-stop-confusing-correlation-with-causationLinks to an external site.

NEEDS TO BE AT LEAST 4-5 PRGRS

2ND RESPONSE/WRIT:

Does good Data guarantee good Decisions?

From the source:

"Global businesses have entered a new era of decision-making. The ability to gather, store, access, and analyze data has grown exponentially over the past decade, and companies now spend tens of millions of dollars to manage the information streaming in from suppliers and customers."

In such a world with access to an abundance of data, is any data-driven decision a perfect decision?

What is the role of judgment? What if our judgment contradicts the data? Is there an accurate recipe for mixing data and judgment?

Does any sort of Data guarantee a good decision, or do we need to be able to find reliable and the most appropriate data?

How about the data analysis technique we use? Is it possible to have different interpretations from the same dataset?

What are other potential challenges to bridging data to good, practical decisions?

:https://hbr-org.ezproxy.lib.utah.edu/Links to an external site.