IIBA Exam CBDA Topic 4 Question 16 Discussion

Actual exam question for IIBA's CBDA exam

Question #: 16
Topic #: 4

[All CBDA Questions]

An analyst is working through data on comparing performance scores in different schools across the state, for ranking purposes. Since there is a lot of data and some extreme outliers, the analyst is trying to determine which type of statistical average would best represent the results. Which of the following is a concern when relying too heavily on summary statistics during data analysis?

AContextualization

BData variation

CData properties

DFrequency

Show Suggested Answer

Suggested Answer: A

Summary statistics are numerical measures that describe certain characteristics of a data set, such as the mean, median, mode, standard deviation, range, or quartiles. Summary statistics can help simplify and communicate complex data, but they can also obscure or distort important information, such as the distribution, shape, outliers, or trends of the data. Contextualization is the process of providing relevant background information, assumptions, limitations, or explanations for the data analysis and its results. Contextualization can help avoid misinterpretation, confusion, or bias when using summary statistics. Contextualization can also help connect the data analysis to the business problem, objectives, and stakeholders.

by Josefa at Jul 05, 2024, 10:35 PM

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Lauran

8 months ago

B is the way to go. You don't want to be that analyst who presents the data like 'everything is fine' when there's actually a lot of craziness going on underneath.

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Miesha

8 months ago

Definitely B. Outliers and skewed data distributions can really throw off your summary stats. Gotta look at the whole picture, not just the averages.

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9 months ago

Option B) Data variation is the key concern. You can't just rely on summary stats like the mean or median without understanding the full distribution of the data.

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