Data Science Analysis in Business Operations Quiz
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Questions and Answers

What is the main purpose of using customer comments about a product in customer service departments?

  • To increase the cost of the product
  • To reduce the number of customers
  • To ignore customer satisfaction
  • To identify aspects for improvement (correct)
  • How are data science tools applied in smart cities?

  • To create more data points
  • To transform data into actions for residents' benefit (correct)
  • To increase pollution
  • To decrease resident satisfaction
  • What is the first dimension of data science activities according to the text?

  • Data Transformation
  • Data Curation
  • Data Flow (correct)
  • Data Analytics
  • What is the main goal of data curation in the context of data science activities?

    <p>To refine collected data</p> Signup and view all the answers

    In which field have recent advances in artificial intelligence allowed diagnosis of diseases when specialists are not available?

    <p>Medical applications</p> Signup and view all the answers

    What does the storage structure of data aim to achieve in the context of data flow?

    <p>Transparency, completeness, and accessibility</p> Signup and view all the answers

    What is one of the important aspects of data science mentioned in the text?

    <p>Extracting actionable insights</p> Signup and view all the answers

    How did the United Parcel Service (UPS) reduce fuel usage and miles off its routes?

    <p>By installing sensors in vans and combining data with GPS information</p> Signup and view all the answers

    What does the Internet Movie Database (IMDB) provide online?

    <p>Data about all elements of the movie industry</p> Signup and view all the answers

    In a supermarket scenario, what do managers gain solid knowledge of by applying data science elements?

    <p>Costs and revenues</p> Signup and view all the answers

    What type of information does IMDB aim to extract using data science tools?

    <p>Information about actors in highest-rated movies</p> Signup and view all the answers

    How did the application of data science tools benefit UPS according to the text?

    <p>Reduced fuel usage and miles off routes</p> Signup and view all the answers

    What does the area under the ROC curve (AUC) measure?

    <p>Efficiency of the model</p> Signup and view all the answers

    Why is it important to translate the output of a regression prediction model into a number?

    <p>To make it easier to understand</p> Signup and view all the answers

    What does the absolute error measure in evaluating a regression model?

    <p>Difference in model's output and desired output</p> Signup and view all the answers

    How is relative error calculated in relation to absolute error?

    <p>(d-y)/d * 100 %</p> Signup and view all the answers

    Why is it mentioned that relative error may not be quite representative for small numbers?

    <p>Small numbers may lead to invalid operations</p> Signup and view all the answers

    Which of the following is NOT a typical metric used to evaluate a regression model?

    <p>Classification error</p> Signup and view all the answers

    What is the purpose of developing a model with a feedback loop that can accommodate changes like product price adjustments?

    <p>To increase the accuracy of the model's predictions.</p> Signup and view all the answers

    In the context of building an intelligent model, what role does the model's confidence in its predictions play?

    <p>It influences end users' actions without verification.</p> Signup and view all the answers

    Why is the 'machine learning canvas' tool helpful in identifying use cases?

    <p>To provide a user-friendly procedure for business managers.</p> Signup and view all the answers

    What does the 'machine learning canvas' tool aim to achieve for business managers?

    <p>Consolidating all steps needed to identify use cases and their value propositions.</p> Signup and view all the answers

    In what scenario could a prediction model be automatically accepted or rejected without contacting an end user?

    <p>When the model's confidence in its predictions is high.</p> Signup and view all the answers

    How does including a feedback loop in a model help in accommodating changes like product price adjustments?

    <p>By allowing for model retraining based on new data.</p> Signup and view all the answers

    What is the purpose of feature selection in machine learning?

    <p>To select informative and relevant features by applying correlation analysis</p> Signup and view all the answers

    Why is it important for features to have a low degree of intercorrelation with other features?

    <p>To make the data more understandable and avoid redundancy</p> Signup and view all the answers

    What role does a domain expert play in feature selection?

    <p>They guide the process and review the list of suggested relevant features</p> Signup and view all the answers

    What is the main purpose of developing a learning mathematical algorithm in machine learning?

    <p>To extract knowledge from data and predict future outcomes</p> Signup and view all the answers

    Which type of analytics is used to understand underlying data patterns in machine learning?

    <p>Descriptive analytics</p> Signup and view all the answers

    How is the learning technique determined in machine learning?

    <p>By choosing between unsupervised and supervised learning based on the nature of the problem</p> Signup and view all the answers

    Study Notes

    ROC Curve and Evaluation Metrics

    • A ROC curve measures the efficiency of a model, with the ideal model being closest to the upper left corner.
    • The area under the curve (AUC) is a measure of efficiency, with an ideal model having an AUC of 1.
    • Regression model evaluation metrics include:
      • Absolute error: the absolute difference between the model's output and the desired output.
      • Relative error: the absolute error normalized with respect to the desired output to obtain a unit-less percentage.

    Data Science Applications

    • Data science is used to extract useful information and make predictions in various industries, such as:
      • Supermarkets: to analyze costs and revenues and predict outcomes of different business scenarios.
      • Logistics: UPS used data science to reduce fuel usage by 8.4 million gallons and shave 85 million miles off its routes.
      • Entertainment: IMDB uses data science to extract information and answer questions about the movie industry.
    • Data science tools can be used to:
      • Identify customer satisfaction and areas for improvement in customer service departments.
      • Improve public transportation systems in smart cities.
      • Diagnose diseases in medical applications using artificial intelligence.

    Data Science Activities

    • Data science activities are conducted in three dimensions: data flow, data curation, and data analytics.
    • Data flow involves collecting, storing, and managing data.
    • Data curation involves refining collected data, including handling changes to data.
    • Data analytics involves extracting insights and making predictions from data.

    Machine Learning

    • Machine learning is used to extract knowledge from data and make predictions.
    • Types of machine learning include:
      • Unsupervised learning: using cluster analysis to learn from data.
      • Supervised learning: using classification and regression approaches to learn from data.
    • Machine learning can be used to:
      • Automate decision-making processes.
      • Identify use cases and achieve value propositions using tools like the machine learning canvas.

    Feature Selection

    • Feature selection involves selecting informative and relevant features from a dataset.
    • Correlation analysis is used to separate redundant features and keep features that show high correlation with the target variable.
    • The result is a reduction in feature sets and more comprehendable data.

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    Description

    Test your knowledge on how data science analysis helps extract useful information and insights for business operations. Learn how data is presented to managers for decision-making in areas like costs, revenues, and future expectations.

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