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IIBA Exam CBDA Topic 2 Question 26 Discussion

Actual exam question for IIBA's CBDA exam
Question #: 26
Topic #: 2
[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?

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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.


Contribute your Thoughts:

Nidia
1 months ago
Haha, relying too heavily on summary stats? That's like driving with your eyes closed and expecting to reach your destination safely.
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Danica
8 days ago
D) Frequency
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Abel
17 days ago
C) Data properties
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Jenelle
18 days ago
B) Data variation
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Lina
20 days ago
A) Contextualization
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Gregg
1 months ago
Hmm, I was leaning towards C) Data properties. Understanding the properties of the data, like skewness or kurtosis, is crucial for selecting the right analysis approach.
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Dick
11 days ago
D: True, but ultimately, all these factors are important to consider when relying on summary statistics for data analysis.
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Gary
17 days ago
C: That's a good point. D) Frequency is also important to consider, as it helps us understand how often certain values occur in the data.
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Tamekia
20 days ago
B: I agree, but I think A) Contextualization is crucial too. We need to consider the context in which the data was collected to make accurate interpretations.
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Malcolm
1 months ago
A: I think B) Data variation is also important to consider. It helps us understand how spread out the data points are.
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Rolf
2 months ago
I agree with Paris. Using summary statistics can overlook important details in the data.
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Paris
2 months ago
I think the concern is data variation.
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Aileen
2 months ago
I agree, B) Data variation is the correct answer. If you just rely on the mean or median, you might miss important nuances in the data.
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Francesco
23 days ago
D) Frequency can be useful in understanding the distribution of values in the data.
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Matilda
1 months ago
C) Data properties can provide insights into the characteristics of the data being analyzed.
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Dorinda
1 months ago
B) Data variation helps to identify the spread and outliers in the data set.
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Trinidad
1 months ago
A) Contextualization is important to understand the data in its proper context.
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Dannie
2 months ago
The key concern here is data variation. Summary statistics can mask the underlying distribution and range of the data.
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Jesusita
2 months ago
C) Data properties
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Goldie
2 months ago
B) Data variation
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Viola
2 months ago
A) Contextualization
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