Data Science Quiz

Which of the following best describes the primary goal of the Data Understanding phase in the data science life cycle?

• Deploying the final model into a production environment.

• Cleaning and transforming the raw data into a usable format.

• Familiarizing oneself with the data, identifying initial patterns, and formulating hypotheses.

• Selecting the most appropriate algorithm for the predictive task.

Which of the following is NOT typically considered a core component of a data science ecosystem?

• Data storage and management systems.

• Programming languages and statistical software.

• Marketing and sales departments.

• Machine learning algorithms and frameworks.

Data science is most accurately differentiated from traditional statistics by its:

• Sole focus on analyzing very large datasets.

• Emphasis on drawing inferences from controlled experiments.

• Strong integration of computational techniques and focus on prediction and automation.

• Exclusive use of visualization techniques for data exploration.

In which of the following domains is data science LEAST likely to be applied?

• Healthcare for disease prediction and diagnosis.

• Finance for fraud detection and risk assessment.

• Literature for analyzing poetic meter and rhyme schemes.

• Transportation for optimizing traffic flow and autonomous driving.

A database containing customer names, addresses, and purchase history organized in tables with defined columns and rows is an example of:

• Unstructured data.

• Semi-structured data.

• Structured data.

• Qualitative data.

Which of the following is an example of unstructured data?

• A spreadsheet of student grades.

• A relational database of product inventory.

• A collection of customer reviews in text format.

• A log file with timestamps and error codes.

Data describing the colors of cars in a parking lot (e.g., red, blue, green) is best categorized as:

• Quantitative and discrete.

• Quantitative and continuous.

• Qualitative and nominal.

• Qualitative and ordinal.

Measurements of the heights of students in a class, recorded in centimeters, represent:

• Qualitative data.

• Quantitative and discrete data.

• Quantitative and continuous data.

• Ordinal data.

The 'Modeling' phase of the data science life cycle primarily involves:

• Communicating the findings to stakeholders.

• Preparing the data for analysis through cleaning and transformation.

• Building and evaluating different machine learning or statistical models.

• Gathering and collecting relevant data from various sources.

Understanding the business problem and defining the objectives is a crucial first step in the data science life cycle because it:

• Determines the computational resources required for the project.

• Ensures that the subsequent data analysis and modeling efforts are aligned with specific goals.

• Dictates the choice of programming languages and software tools.

• Primarily focuses on identifying potential data sources.