12: Answer Key
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- 12.0: Chapter 1
- This page emphasizes the importance of data preparation for analysis, advocating for the storage of data on servers over local computers, particularly within cloud-based systems. It also illustrates a biologist's use of extensive genetic datasets to gain insights into the genetic underpinnings of diseases.
- 12.1: Chapter 3
- This page outlines a set of quantitative problems featuring statistical measures such as mean (16.4), trimmed mean (12.9), median (4.1), range (8.7), standard deviation (2.5), and variance (6.5). It includes information on quartiles, interquartile range (795.97), outlier detection (4303.76), percentiles, z-scores, and probability scenarios. Reference is made to a solution manual for additional insights.
- 12.2: Chapter 5
- This page covers quantitative problems in time series analysis, including sales cycle periods, identifying peaks and minima for periodicity, and calculating centered Simple Moving Averages (SMA) and trend-cycle components. It discusses methods for addressing missing data, forecasting future values, and assessing model performance metrics such as MAE, RMSE, MAPE, and sMAPE, with specific numerical forecasts and calculations given.
- 12.4: Chapter 7
- This page discusses the learning capabilities of networks for recognizing patterns, focusing on Convolutional Neural Networks (CNNs) for image data, their effectiveness in classification and detection, and the importance of algorithms for hands-free interaction and accessibility. It also highlights ethical concerns related to the design of virtual assistants that may gather personal data without user consent.
- 12.5: Chapter 8
- This page discusses key concepts in research ethics, data security, and model accuracy in data science. It stresses the importance of informed consent, secure data management, and legal compliance. The content includes types of data, strong security protocols, and strategies to prevent bias and overfitting in models. Additionally, it highlights the necessity for accessibility and inclusivity regarding all individuals involved in data handling.
- 12.6: Chapter 10
- This page emphasizes the essentials of effective communication in technical fields, covering concise summaries, appropriate use of jargon, and audience connection. Key points include clarity in presentations, practical applications, model performance insights, and the robustness of testing results. It highlights the importance of summarizing complex analyses for diverse backgrounds and underscores the role of persuasion in conveying business issues and research significance.