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Exam IIBA-CBDA topic 1 question 14 discussion

Actual exam question from IIBA's IIBA-CBDA
Question #: 14
Topic #: 1
[All IIBA-CBDA Questions]

The marketing department for a major restaurant chain is interested in testing a Kids Eat Free campaign to determine if it will help to increase sales. They are interested in piloting the campaign to determine which day of the week will improve sales the most. The campaign is launched across 7 cities with each city promoting a different day of the week. The sales data is collected and provided to a team for analysis.
What concern might the analytics team have regarding data quality across cities?

  • A. Variation
  • B. Linearity
  • C. Normality
  • D. Heteroskedacity
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Suggested Answer: A 🗳️
by Rabbitsfoot at July 17, 2024, 5:48 p.m.

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keyss
3 weeks, 3 days ago
Selected Answer: A
A. Variation
upvoted 1 times
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Rabbitsfoot
6 months ago
Selected Answer: A
OK! The answer is in fact A. See pg 123 in the CBDA guide on .2 Inferential Statistics. Yes, the excerpt from the CBDA guide aligns well with the answer. Here's how: Variation: INITIALLY, the analytics team would be concerned with variation to understand the differences in sales data across the cities. This is a fundamental step to ensure that any observed differences are understood in the context of the campaign. Heteroskedasticity: AFTER collecting and analyzing the data, examining for heteroskedasticity would be appropriate. Heteroskedasticity refers to the situation where the variance of residuals (or errors) is not constant across all levels of the independent variable. This could reveal if the variability in sales is consistent or if it varies significantly across different days or cities.
upvoted 3 times
Rabbitsfoot
6 months ago
The guide discusses heteroskedasticity as having error residuals with varying variance, which is a more advanced concern after initial data analysis shows variation. So, focusing on variation first and then checking for heteroskedasticity aligns with the correct approach for ensuring data quality and understanding the data thoroughly.
upvoted 1 times
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Rabbitsfoot
6 months, 3 weeks ago
Selected Answer: D
See CBDA guide pg 152 - Heteroskedasticity refers to having error residuals that do not have a constant variance. It indicates that the data behaves differently across different ranges of values.
upvoted 1 times
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