IASSC Exam ICBB Topic 5 Question 37 Discussion

Actual exam question for IASSC's ICBB exam

Question #: 37
Topic #: 5

[All ICBB Questions]

Which statement(s) are correct about the Regression shown here? (Note: There are 2 correct answers).

AThe dependent variable is the outside temperature

BThe relationship between outside temperature and number of customers per hour is a Linear Regression

CThe dashed lines indicate with 95% confidence where all of the process data should fall between

DThe dashed lines indicate with 95% confidence the estimate for the Quadratic Regression Line

EThe predicted number of customers per hour is close to 5 if the outside temperature is 10 deg C

Show Suggested Answer

Suggested Answer: C

by Donte at Sep 16, 2022, 11:27 AM

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Micah

2 months ago

Hmm, I'm not sure about the outside temperature being the dependent variable. Shouldn't it be the other way around? But I agree with B and C. This is a tricky one!

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Teddy

7 days ago

User4: The dashed lines indicate with 95% confidence where all of the process data should fall between.

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Laquanda

13 days ago

User3: The relationship between outside temperature and number of customers per hour is a Linear Regression.

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Joni

16 days ago

User2: I agree, that makes more sense.

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Valentin

26 days ago

User 3: The relationship between outside temperature and number of customers per hour is a Linear Regression.

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Tyra

1 months ago

User 2: I think you're right, the outside temperature is the independent variable.

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Naomi

1 months ago

User 1: The dependent variable is actually the number of customers per hour.

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Shala

2 months ago

User1: I think the dependent variable is the number of customers per hour.

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Glen

2 months ago

I'm not sure about the quadratic regression part, but I agree that the relationship is linear and the dashed lines show the 95% confidence interval. This is a pretty straightforward question.

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Dan

2 months ago

I think the correct answers are B and C. The relationship looks linear, and the dashed lines indicate the 95% confidence interval for the regression line.

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