IIBA Exam CBDA Topic 1 Question 3 Discussion

Actual exam question for IIBA's CBDA exam

Question #: 3
Topic #: 1

[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 Bulah at Mar 05, 2024, 05:51 AM

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Gaston

1 day ago

Totally agree, data variation is key!

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Lorriane

7 days ago

Summary stats can miss important context!

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Lashanda

13 days ago

Frequency seems less relevant to summary statistics, but I could be wrong. I need to think more about how they all relate.

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Nichelle

19 days ago

I practiced a similar question, and I feel like data properties might be the key concern since they affect how we interpret the averages.

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Vanesa

24 days ago

I think contextualization is important too, but I’m not sure if it’s the main issue when looking at summary stats.

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Colette

30 days ago

I remember we discussed how outliers can skew the mean, so maybe data variation is a concern here?

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Lashawnda

1 month ago

I'm a little confused by this question. I'm not sure if the right answer is B or C. Both of those options seem relevant to the issue of relying too much on summary stats. I'll have to think this through carefully before selecting an answer.

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Trina

1 month ago

Hmm, this is a tricky one. I'm not totally sure what the right answer is, but I'm leaning towards B - data variation. Seems like the question is getting at how summary stats can miss important details about the distribution of the data.

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Pok

1 month ago

This question is asking about the limitations of relying too heavily on summary statistics. I think the key is to consider how the data can vary and how that variation might not be fully captured by just looking at averages or other central tendency measures.

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Robt

1 month ago

Okay, I've got this. The answer has to be B - data variation. When you're working with a lot of data and outliers, the summary stats might not tell the whole story. You need to look at how the data is distributed to really understand what's going on.

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Rodrigo

1 month ago

Okay, I think I've got it. The highlighted color and the key combinations to identify the selector are different between Windows and SAP. I'll make sure to remember that.

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Leandro

1 month ago

I'm pretty confident on this one. Listening involves more than just hearing - it's about actively attending and providing feedback to the speaker.

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Willard

1 month ago

I feel confident about this question. The key is to identify the options that correctly reference the existing BOOK_SEQ sequence and have the appropriate column definitions.

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Ernestine

1 month ago

I lean towards option A, but I remember there being exceptions. It might be possible for the bank to unintentionally participate if they didn't fully vet anything. It's tricky!

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Charlena

1 year ago

I agree. It's important to take into account both contextual information and data variation when analyzing data.

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Dorsey

1 year ago

Definitely. Data variation can impact the choice of average and help account for outliers skewing the results.

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Shasta

1 year ago

But what about data variation? Isn't that also important to consider when choosing the right statistical average?

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Ulysses

1 year ago

That's true. The context in which the data was collected is crucial for proper interpretation.

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Charlena

2 years ago

I think relying too heavily on summary statistics can lead to overlooking important contextual information.

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