Many times, data are missing because of various reasons. This poses some challenges when doing data analysis.

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Many times, data are missing because of various reasons. This poses some challenges when doing data analysis. For example, suppose you wanted to do some analysis of the yearly incomes of the faculty at GCU. When asked for their incomes, 25% of the faculty did not participate in the survey; therefore, their incomes are missing from the dataset.

How would you summarize the income data in this case?

Is it appropriate to ignore the missing incomes and summarize the data without them?

Should you estimate the missing incomes, perhaps with the overall average, to complete the data set?

Related Book For answer-question

Computer Networking A Top-Down Approach

ISBN: 978-0136079675

5th edition

Authors: James F. Kurose, Keith W. Ross

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Posted Date: May 13, 2023 11:23 PM

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Many times, data are missing because of various reasons. This poses some challenges when doing data analysis.

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Computer Networking A Top-Down Approach

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