## LyraElizabethAdams 3 years ago PLEASE HELP!!!! Please explain why this is FALSE: "5. Using data from Boston, Massachusetts, a test of independence is run on the claim that ice cream sales per month and the number of car wrecks per month are independent. The claim is rejected. Using number of car wrecks as the x variable and ice cream sales as the y variable, an r value of r=0.923 is then computed and shown to exceed the critical value for this data. The data is double checked and verified. This shows that car wrecks cause ice cream sales."

1. jim_thompson5910

That r value is the key here

2. jim_thompson5910

usually when it's this high (regardless of the critical value), it implies there's a strong correlation between the two variables

Okay

Oh, yes - I do remember learning that.

5. jim_thompson5910

a strong correlation corresponds to the two variables being linked (one is independent and the other is dependent on that independent variable)

Makes sense, so far.

7. jim_thompson5910

so they can't be independent if they are linked like this

8. jim_thompson5910

that's why the claim that they are independent is rejected

Oh, I think I see what you're meaning - because the correlation (relationship) between "x" and "y" is so strong, both variables are dependent on each other, so it is not possible that they could be independent of each other?

10. jim_thompson5910

that is close, it's more like "one variable dictates what the other variable is...so one variable is independent while the other depends on the first variable"

Okay

12. jim_thompson5910

but yes, they are linked in a way that they can't be independent of each other

So, if the problem IS correct to have rejected the claim, what part of the problem is incorrect?

14. jim_thompson5910

I'm not sure what you mean

15. jim_thompson5910

oh i know what you're asking

Well, the instructions for the problem say it is false. I'm supposed to explain why it's false.

17. jim_thompson5910

this is a very dangerous part of statistics because students often confuse correlation and causation

18. jim_thompson5910

this is very important not to mix the two

19. jim_thompson5910

if two variables are strongly correlated with each other, it doesn't necessarily mean that one causes the other

I should probably let you know that the last part of the problem says: NOTE: While this specific r-value is made up, this general pattern has been shown in several real world data sets involving ice cream sales and number of car wrecks in major cities on the east coast of the United States.

21. jim_thompson5910

ie correlation does NOT imply causation

I'm not sure if the NOTE is true or false (I don't know if my professor is saying that this part is false or true.

23. jim_thompson5910

just because they both tend to decrease (for instance), doesn't mean that one causes the other to decrease as it decreases

24. jim_thompson5910

does that make sense?

Yes! Thank you so much! I really appreciate that you took your time to help me! :) I understand it.

26. jim_thompson5910

you're welcome