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Principles of Data Science

Chapter 10

Principles of Data ScienceChapter 10

Chapter Review

1.
c. Concise with a focus on summaries and outcomes
2.
b. Technical jargon
3.
b. Connecting with diverse audiences through tailored communication
4.
b. Practical application and procedures
5.
a. To provide different levels of detail for various audiences
6.
c. To clarify and accentuate significant data insights
7.
d. With clear labels, titles, and straightforward explanations
8.
b. To steer the decision-making process
9.
b. It is specific and verifiable.
10.
b. Seventy-five percent of the variance in housing prices is explained by the model.
11.
b. To understand the model's performance more deeply
12.
a. To test the robustness of results against input variability
13.
c. To summarize complex analyses for an audience of varied backgrounds
14.
b. An introduction to the business problem or research question
15.
b. The novelty or relevance of the approach
16.
a. With a persuasive call to action
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© Dec 19, 2024 OpenStax. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike License . The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the Creative Commons license and may not be reproduced without the prior and express written consent of Rice University.