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Mastering Data Science Ethics: SNHU DAT 250 Exam 2025 - 160 Answered Questions, Exams of Social Statistics and Data Analysis

Buckinghamshire New UniversitySocial Statistics and Data Analysis

This study guide provides a comprehensive overview of ethical considerations in data science, covering key topics such as data governance, privacy laws, and ethical frameworks. It includes 160 answered questions to help students prepare for the snhu dat 250 exam. The guide emphasizes the importance of understanding ethical principles in data handling and their application in real-world scenarios.

Typology: Exams

2024/2025

Available from 04/12/2025

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MASTERING DATA SCIENCE ETHICS: SNHU DAT 250
EXAM 2025 – 160 ANSWERED QUESTIONS
Comprehensive Study Guide with Expert Answers, Key Concepts, and
Strategies for Success
Study Guide Overview:
Course Focus:
DAT 250 delves into the ethical considerations in data science, emphasizing data governance, privacy, and the
societal impact of data-driven decisions.
Key Topics to Master:
• Data Governance and Compliance: Understand the principles of data management and the importance
of compliance audits in ethical data handling.
• Ethical Frameworks: Familiarize yourself with frameworks like the DAMA Guide's 15 principles for
data security management.
• Privacy Laws and Regulations: Study the implications of laws such as GDPR and how they affect data
collection and usage.
• Case Studies: Analyze real-world scenarios to understand the application of ethical principles in data
science.
Study Strategies:
• Flashcards: Utilize platforms like Quizlet to reinforce key terms and concepts.
• Practice Questions: Review the 160 answered questions to identify patterns and commonly tested topics.
• Discussion Participation: Engage in course discussions to deepen understanding and gain diverse
perspectives.
• Supplementary Resources: Explore additional materials such as the DAMA Guide and relevant case
studies to broaden your knowledge base.
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Download Mastering Data Science Ethics: SNHU DAT 250 Exam 2025 - 160 Answered Questions and more Exams Social Statistics and Data Analysis in PDF only on Docsity!

MASTERING DATA SCIENCE ETHICS: SNHU DAT 250

EXAM 2025 – 160 ANSWERED QUESTIONS

Comprehensive Study Guide with Expert Answers, Key Concepts, and

Strategies for Success

Study Guide Overview: Course Focus: DAT 250 delves into the ethical considerations in data science, emphasizing data governance, privacy, and the societal impact of data-driven decisions. Key Topics to Master:

  • Data Governance and Compliance: Understand the principles of data management and the importance of compliance audits in ethical data handling.
  • Ethical Frameworks: Familiarize yourself with frameworks like the DAMA Guide's 15 principles for data security management.
  • Privacy Laws and Regulations: Study the implications of laws such as GDPR and how they affect data collection and usage.
  • Case Studies: Analyze real-world scenarios to understand the application of ethical principles in data science. Study Strategies:
  • Flashcards: Utilize platforms like Quizlet to reinforce key terms and concepts.
  • Practice Questions: Review the 160 answered questions to identify patterns and commonly tested topics.
  • Discussion Participation: Engage in course discussions to deepen understanding and gain diverse perspectives.
  • Supplementary Resources: Explore additional materials such as the DAMA Guide and relevant case studies to broaden your knowledge base.

QUESTIONS AND ANSWERS

  1. What is the primary focus of rule utilitarianism in ethical decision-making? The consequences of the action. The intentions behind the action. The rights of individuals affected by the action. The adherence to absolute moral laws.
  2. How do negative rights differ from positive rights in terms of obligations? Negative rights require others to abstain from interfering with individual liberties, while positive rights require others to provide certain benefits. Negative rights are only applicable in democratic societies, while positive rights are universal. Negative rights are always prioritized over positive rights in legal systems. Negative rights are seen as entitlements, while positive rights are seen as liberties.
  3. What type of data is characterized by organized rows and columns, as seen in an Excel spreadsheet? Semi-structured Structured Raw Unstructured
  4. What is a primary reason businesses prefer opt-out consent models? Higher user engagement
  1. Freedom of speech: does not apply to symbolic speech exists to solely protect orthodox ideas Is absolute is not absolute
  2. What is the main purpose of collaborative filtering in data science? To ensure ethical data sharing practices. To predict what one person may prefer based on the preferences of large numbers of people. To analyze structured data for statistical insights. To visualize data trends over time.
  3. Describe how an IT manager supports data science teams in their operations. An IT manager primarily focuses on data analysis and visualization tasks. An IT manager supports data science teams by building and updating IT environments and monitoring operations and resource usage. An IT manager is responsible for creating machine learning models. An IT manager ensures that data is collected without any ethical considerations.
  4. Consider a scenario where a government decides to ban certain types of online speech. Based on the principles discussed, under what condition could this ban be considered justified? If the ban is popular among citizens

If the ban is enforced by law enforcement agencies If the ban is temporary If the ban results in greater public good

  1. Which of these answers best describes one of the ways secondary source information is useful to marketers? It can be a source of insight into users of their category of products or services It can provide detailed user data they can re-analyze as needed It can be tailored to address their specific questions
  2. Describe the significance of explicit consent in the opt-in model of data sharing. Explicit consent ensures that consumers are aware and agree to the sharing of their information, aligning with privacy advocacy. Explicit consent is only required for sensitive data. Explicit consent allows organizations to share data without consumer knowledge. Explicit consent is not necessary in data sharing practices.
  3. Describe the characteristics that differentiate semi-structured data from structured and unstructured data. Semi-structured data contains organizational properties but lacks a strict schema, unlike structured data which is highly organized and unstructured data which has no predefined format. Semi-structured data is completely unorganized and has no identifiable format.

Misinformation could be disseminated to the public, damaging credibility. The report would be published faster without any issues. The team would save resources and time.

  1. A subset of AI, explains the application of AI using algorithms and data in order to allow the computer to learn without being programmed for a specific task. Deep Learning Machine learning Artificial Intelligence Algorithms
  2. In a scenario where a data science team is tasked with improving customer satisfaction, how would data mining be utilized in their approach? By gathering and scoping relevant customer feedback and interaction data. By implementing strict data governance policies. By developing predictive models based on historical sales data. By visualizing customer satisfaction trends over time.
  3. Which of the following was an effect of the invention of the printing press? The spread of information around the world slowed down. Hand-copied texts were in even greater demand. While more books could be produced, it was still only the wealthy who could afford them.

Books and other forms of writing became more accessible to non-elites.

  1. If a dataset contains numerous missing values and inconsistencies, what steps should a data scientist take to prepare the data for analysis? Collect more data without fixing the existing issues. Immediately apply machine learning algorithms without any preprocessing. Perform data cleaning to fix inconsistencies and handle missing values. Visualize the data without addressing the inconsistencies.
  2. Describe how microtargeting utilizes data to influence voter outreach strategies. Microtargeting is based on public speeches and rallies to attract voters. Microtargeting uses voter registration, frequency, and consumer data to tailor messages to likely supporters. Microtargeting focuses on random sampling of voters to create outreach strategies. Microtargeting relies solely on social media interactions to gauge voter interest.
  3. In a scenario where a data scientist must decide whether to share sensitive data, how might rule utilitarianism guide their decision compared to act utilitarianism? Rule utilitarianism would prioritize individual actions over guidelines, while act utilitarianism would rely on moral rules. Rule utilitarianism would suggest following established ethical guidelines for data sharing, while act utilitarianism would focus on the specific consequences of sharing that data.

Open source notebooks Database management systems Traditional spreadsheets

  1. What type of data is characterized by its highly organized format that allows for easy processing? Semi-structured data Structured data Unstructured data Raw data
  2. If a data science manager fails to balance team development with project planning, what potential issue could arise in a data science project? Successful project completion ahead of schedule Increased data accuracy Enhanced team collaboration Project delays due to lack of coordination
  3. Freedom of expression Can be limited in some circumstances Can be limited by the government but not by the private sector None of these Is absolute in all circumstances
  4. Email is representative of which of the following types of data? Mined Structured

Unstructured Coded

  1. Consider a scenario where a data scientist decides to share sensitive data without consent. How does the first formulation of the Categorical Imperative apply to this situation? The data scientist can decide based on personal judgment without considering others. As long as the data is anonymized, it can be shared freely. If sharing sensitive data without consent is wrong for one person, it should be wrong for everyone. It is acceptable if it benefits the majority, regardless of consent.
  2. Describe the role of a data science manager in balancing team development and project management. The data science manager is primarily involved in data collection processes. The data science manager only focuses on technical development without project oversight. The data science manager is responsible for team building while ensuring effective project planning and monitoring. The data science manager delegates all responsibilities to team members.
  3. Describe the process involved in predictive modeling as outlined in the text. It involves analyzing ethical implications of data usage. It involves creating visual representations of data. It involves collecting raw data and storing it in databases.

Secondary source Tertiary source

  1. People live together in society in accordance with an agreement that establishes moral and political rules of behavior social contract theory force theory divine right theory evolutionary theories
  2. The suppression of art and other forms of communication considered to be objectionable or harmful for moral, political, or religious reasons is called? censorship appropriation ethical values ethical judgement
  3. In a scenario where a dataset contains numerous missing values, which step of the Data Science Lifestyle would you prioritize to ensure effective analysis? Data Visualization Feature Engineering Predictive Modeling Data Cleaning
  4. What are the two main contributions of a business manager in data science? Develop the problem and develop a strategy of analysis

Collect data and ensure data quality Analyze data and visualize results Implement machine learning algorithms and manage IT infrastructure

  1. Describe the role of open source notebooks in the workflow of a data scientist. Open source notebooks are used to create ethical guidelines for data usage. Open source notebooks facilitate the writing and execution of code while allowing for data visualization in a single environment. Open source notebooks are primarily used for data storage and management. Open source notebooks are tools for only statistical analysis.
  2. Describe how data visualization can enhance the communication of data findings. Data visualization is only useful for technical audiences who understand data. Data visualization complicates the data analysis process by adding unnecessary graphics. Data visualization enhances communication by presenting complex data in an accessible format that highlights key insights. Data visualization serves no purpose in communicating findings.
  3. Describe the implications of government monopolization on information dissemination in society. Government monopolization enhances media diversity.

Being the best version of yourself and reaching your highest potential. Ensuring that actions are universally applicable to all individuals.

  1. Discuss the limitations of the Freedom of Expression in the context of ethical governance. The Freedom of Expression is only limited by government regulations. The Freedom of Expression has limitations to protect other rights and societal interests. The Freedom of Expression is unrestricted and cannot be limited. The Freedom of Expression is absolute in all circumstances.
  2. Companies prefer the _____ model of information consent sign-out opt-out opt-in sign-up
  3. What is the primary method used in explicit filtering for collaborative filtering? Analyzing user browsing history Using demographic data Tracking user purchases Asking people to rank preferences
  1. What determines whether an action is considered good or bad in Act Utilitarianism? The benefits exceed the harms for good actions, and the harms exceed the benefits for bad actions. The action is good if it follows a moral rule. The action is good if it maximizes individual rights. The action is judged based on its adherence to societal norms.
  2. What is one of the primary responsibilities of a data science manager? Conducts data analysis Designs data visualization tools Oversees the data science team Develops machine learning algorithms
  3. Which of the following best describes an absolute right? Absolute Rights require a balance between the rights of the individual and the needs of the wider community or state interest Absolute Rights are justicable and so complaints about a breach of absolute human rights can only be heard in a jury court Absolute Rights can never be interfered with by the government in any circumstances Absolute Rights are the rights guaranteed by judgements made in the Supreme Court of Human Rights Absolute Rights are a legal fiction used to illustrate an ideal relationship between indendant agents e.g. the person and the state
  4. Describe the significance of the 'Data Cleaning' step in the Data Science Lifestyle.
  1. Secondary use research is: Research that generates at least two publications. Research that relies on information originally collected for a purpose other than the current research purpose. Original research that is copied by a second researcher.
  2. Which of these options is true of unstructured data? It has no value whatsoever in data analytics It is data that is easily searchable Technology attempting to capture unstructured data is in the advanced stage Spreadsheet is an example of unstructured data Emails, videos, social media postings are examples of, and roughly 80% of data is, unstructured data
  3. Describe the significance of data mining in the context of a data science project. Data mining is the process of cleaning data for better accuracy. Data mining is primarily focused on visualizing data results for stakeholders. Data mining is about developing machine learning algorithms to predict outcomes. Data mining is crucial as it involves gathering and scoping the necessary data, which forms the foundation for analysis and decision-making.
  4. Describe the key features that differentiate structured data from unstructured data.

Structured data is less reliable than unstructured data due to its fixed format. Structured data is highly organized and can be processed in a fixed format, while unstructured data lacks a predefined structure and is more difficult to analyze. Structured data requires no specific tools for processing, unlike unstructured data. Structured data is always numerical, whereas unstructured data is always textual.

  1. Describe how the printing press changed the landscape of information dissemination in society. The printing press only benefited religious institutions in spreading their messages. The printing press made it easier for governments to control the flow of information. The printing press allowed private individuals to broadcast their ideas to a wide audience, reducing the control of governments and religious institutions. The printing press had no significant impact on information dissemination.
  2. Describe how Google's Personalized Search can be considered a secondary source in the context of data usage. Google's Personalized Search only uses data from social media platforms, which makes it a secondary source. Google's Personalized Search uses collected data from users' search queries and web pages to inform companies for marketing purposes, making it a secondary source of information.