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LyraElizabethAdams

  • 2 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."

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  1. jim_thompson5910
    • 2 years ago
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    That r value is the key here

  2. jim_thompson5910
    • 2 years ago
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    usually when it's this high (regardless of the critical value), it implies there's a strong correlation between the two variables

  3. LyraElizabethAdams
    • 2 years ago
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    Okay

  4. LyraElizabethAdams
    • 2 years ago
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    Oh, yes - I do remember learning that.

  5. jim_thompson5910
    • 2 years ago
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    a strong correlation corresponds to the two variables being linked (one is independent and the other is dependent on that independent variable)

  6. LyraElizabethAdams
    • 2 years ago
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    Makes sense, so far.

  7. jim_thompson5910
    • 2 years ago
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    so they can't be independent if they are linked like this

  8. jim_thompson5910
    • 2 years ago
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    that's why the claim that they are independent is rejected

  9. LyraElizabethAdams
    • 2 years ago
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    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
    • 2 years ago
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    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"

  11. LyraElizabethAdams
    • 2 years ago
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    Okay

  12. jim_thompson5910
    • 2 years ago
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    but yes, they are linked in a way that they can't be independent of each other

  13. LyraElizabethAdams
    • 2 years ago
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    So, if the problem IS correct to have rejected the claim, what part of the problem is incorrect?

  14. jim_thompson5910
    • 2 years ago
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    I'm not sure what you mean

  15. jim_thompson5910
    • 2 years ago
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    oh i know what you're asking

  16. LyraElizabethAdams
    • 2 years ago
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    Well, the instructions for the problem say it is false. I'm supposed to explain why it's false.

  17. jim_thompson5910
    • 2 years ago
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    this is a very dangerous part of statistics because students often confuse correlation and causation

  18. jim_thompson5910
    • 2 years ago
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    this is very important not to mix the two

  19. jim_thompson5910
    • 2 years ago
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    if two variables are strongly correlated with each other, it doesn't necessarily mean that one causes the other

  20. LyraElizabethAdams
    • 2 years ago
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    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
    • 2 years ago
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    ie correlation does NOT imply causation

  22. LyraElizabethAdams
    • 2 years ago
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    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
    • 2 years ago
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    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
    • 2 years ago
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    does that make sense?

  25. LyraElizabethAdams
    • 2 years ago
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    Yes! Thank you so much! I really appreciate that you took your time to help me! :) I understand it.

  26. jim_thompson5910
    • 2 years ago
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    you're welcome

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