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LyraElizabethAdams
Group Title
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."
 2 years ago
 2 years ago
LyraElizabethAdams Group Title
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."
 2 years ago
 2 years ago

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jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
That r value is the key here
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
usually when it's this high (regardless of the critical value), it implies there's a strong correlation between the two variables
 2 years ago

LyraElizabethAdams Group TitleBest ResponseYou've already chosen the best response.0
Okay
 2 years ago

LyraElizabethAdams Group TitleBest ResponseYou've already chosen the best response.0
Oh, yes  I do remember learning that.
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
a strong correlation corresponds to the two variables being linked (one is independent and the other is dependent on that independent variable)
 2 years ago

LyraElizabethAdams Group TitleBest ResponseYou've already chosen the best response.0
Makes sense, so far.
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
so they can't be independent if they are linked like this
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
that's why the claim that they are independent is rejected
 2 years ago

LyraElizabethAdams Group TitleBest ResponseYou've already chosen the best response.0
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?
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
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"
 2 years ago

LyraElizabethAdams Group TitleBest ResponseYou've already chosen the best response.0
Okay
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
but yes, they are linked in a way that they can't be independent of each other
 2 years ago

LyraElizabethAdams Group TitleBest ResponseYou've already chosen the best response.0
So, if the problem IS correct to have rejected the claim, what part of the problem is incorrect?
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
I'm not sure what you mean
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
oh i know what you're asking
 2 years ago

LyraElizabethAdams Group TitleBest ResponseYou've already chosen the best response.0
Well, the instructions for the problem say it is false. I'm supposed to explain why it's false.
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
this is a very dangerous part of statistics because students often confuse correlation and causation
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
this is very important not to mix the two
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
if two variables are strongly correlated with each other, it doesn't necessarily mean that one causes the other
 2 years ago

LyraElizabethAdams Group TitleBest ResponseYou've already chosen the best response.0
I should probably let you know that the last part of the problem says: NOTE: While this specific rvalue 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.
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
ie correlation does NOT imply causation
 2 years ago

LyraElizabethAdams Group TitleBest ResponseYou've already chosen the best response.0
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.
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
just because they both tend to decrease (for instance), doesn't mean that one causes the other to decrease as it decreases
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
does that make sense?
 2 years ago

LyraElizabethAdams Group TitleBest ResponseYou've already chosen the best response.0
Yes! Thank you so much! I really appreciate that you took your time to help me! :) I understand it.
 2 years ago

jim_thompson5910 Group TitleBest ResponseYou've already chosen the best response.1
you're welcome
 2 years ago
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