Data Science MCQs with answers Page - 135

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Q. What does the acronym "API" stand for in the context of data and software integration?

  • (A) Application Programming Interface
  • (B) Advanced Programming Integration
  • (C) Algorithmic Programming Interface
  • (D) Automated Program Integration

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Q. In the context of data analysis, what is the primary goal of hypothesis testing?

  • (A) To visualize data
  • (B) To summarize data
  • (C) To build predictive models
  • (D) To determine if there is a significant difference or effect

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Q. What statistical technique is used to estimate population parameters from a sample of data?

  • (A) Descriptive statistics
  • (B) Exploratory data analysis
  • (C) Inferential statistics
  • (D) Data preprocessing

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Q. What is the term for the process of finding and correcting errors in a dataset?

  • (A) Data transformation
  • (B) Data cleaning
  • (C) Data aggregation
  • (D) Data transformation

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Q. In data science, what does the acronym "ETL" stand for?

  • (A) Encode, Tokenize, Leverage
  • (B) Estimate, Test, Label
  • (C) Extract, Transform, Load
  • (D) Explore, Train, Learn

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Q. What is the primary goal of A/B testing in data analysis?

  • (A) To create visualizations
  • (B) To build predictive models
  • (C) To collect more data
  • (D) To compare two versions of a webpage or product to determine which one performs better

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Q. In the context of machine learning, what is the purpose of regularization techniques such as L1 and L2 regularization?

  • (A) To prevent overfitting by adding a penalty term to the loss function
  • (B) To remove outliers from the data
  • (C) To increase model complexity
  • (D) To reduce dimensionality

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Q. What is the term for the process of converting categorical data into numerical form for machine learning?

  • (A) Data normalization
  • (B) Text vectorization
  • (C) Feature scaling
  • (D) One-hot encoding

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Q. Which statistical test is used to determine if there is a significant association between two categorical variables?

  • (A) Chi-squared test
  • (B) T-test
  • (C) ANOVA
  • (D) Regression analysis

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Q. In the context of data ethics, what does "bias mitigation" refer to?

  • (A) Increasing the sample size
  • (B) Improving model accuracy
  • (C) Removing outliers from a dataset
  • (D) Reducing biases in data collection

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