How Well Do You Know About Data Science? Data Science Quiz

25 Questions | Total Attempts: 7389

SettingsSettingsSettings
How Well Do You Know About Data Science? Data Science Quiz - Quiz

Data science deals with processes and systems, which are used to extract knowledge or insights from large amounts of data. Data extracted can be either structured or unstructured and can be used to form conclusions. Test out what you know about data science by taking up the quiz below. All the best!


Questions and Answers
  • 1. 
    Which of the following model is usually gold standard for data analysis?
    • A. 

      Inferential

    • B. 

      Descriptive

    • C. 

      Casual

    • D. 

      All of the mentioned

  • 2. 
    Which of the following are  “Measures of Central Tendency”?
    • A. 

      Mean,Range, Mode

    • B. 

      Mean, Standard Deviation, Range

    • C. 

      Mode, Mean, Median

    • D. 

      Range, Standard Deviation, Variance

  • 3. 
    Who is a data scientist?
    • A. 

      Mathematician

    • B. 

      Statistician

    • C. 

      Software programmer

    • D. 

      All of the above

  • 4. 
    Which of the following is performed by Data Scientist?
    • A. 

      Define the question

    • B. 

      Create reproducible code

    • C. 

      Challenge results

    • D. 

      All of the Mentioned

  • 5. 
    Which of the following is one of the key data science skill?
    • A. 

      Statistics

    • B. 

      Machine learning

    • C. 

      Data visualization

    • D. 

      All of the mentioned

  • 6. 
    Raw data should be processed only one time.
    • A. 

      True

    • B. 

      False

  • 7. 
    Which of the following is characteristic of Processed Data?
    • A. 

      Data is not ready for analysis

    • B. 

      All steps should be noted

    • C. 

      Hard to use for data analysis

    • D. 

      None of the mentioned

  • 8. 
    Which of the following testing is concerned with making decisions using data?
    • A. 

      Probability

    • B. 

      Hypothesis

    • C. 

      Casual

    • D. 

      None of the mentioned

  • 9. 
    Which of the following of a random variable is a measure of spread?
    • A. 

      Variance

    • B. 

      Standard deviation

    • C. 

      Empirical mean

    • D. 

      All of the mentioned

  • 10. 
    Which of the following technique comes under practical machine learning?
    • A. 

      Decision Tree

    • B. 

      Data Visualisation

    • C. 

      Forecasting

    • D. 

      None of the mentioned

  • 11. 
    Which of the following is definition of Raw Data?
    • A. 

      Set of Measurement on Recorded Values

    • B. 

      Processed Data

    • C. 

      Easy to use for data analysis

    • D. 

      None of the Mentioned

  • 12. 
    __________ is the standard deviation of a sampling distribution.
    • A. 

      Sample error

    • B. 

      Sampling error

    • C. 

      Simple error

    • D. 

      Standard error

  • 13. 
    Which of the following diagram is used to view correlation?
    • A. 

      Triangle

    • B. 

      Boxplot

    • C. 

      Corrgram

    • D. 

      Histogram

  • 14. 
    ____________ is a multidisciplinary which involves extraction of knowledge from large volumes of data that are structured or unstructured.
    • A. 

      Data Science

    • B. 

      Data Analysis

    • C. 

      Descriptive Analysis

    • D. 

      None of the mentioned

  • 15. 
    Pick Lazy Algorithm
    • A. 

      K-Mean

    • B. 

      CNN

    • C. 

      KNN

    • D. 

      RNN

  • 16. 
    3V’s in Big Data
    • A. 

      Velocity, Victory, Volume

    • B. 

      Volume, Velocity, Variety

    • C. 

      Volume, Viscous, Velocity

    • D. 

      None of the above

  • 17. 
    Positive Correlation:
    • A. 

      Above -0.8

    • B. 

      Below -0.8

    • C. 

      Above 0.8

    • D. 

      Below 0.65

  • 18. 
    Weighted Average is used in:
    • A. 

      Classification

    • B. 

      Regression

    • C. 

      Forecasting

    • D. 

      Above All

  • 19. 
    Sequential Modelling is done on
    • A. 

      CNN

    • B. 

      KNN

    • C. 

      RNN

    • D. 

      ANN

  • 20. 
    Why Machine Learning in Data Science?
    • A. 

      For Visualization

    • B. 

      For Prediction

    • C. 

      For Cleaning

    • D. 

      All the above

  • 21. 
    Tableau can create worksheet-specific filters.
    • A. 

      True

    • B. 

      False

  • 22. 
    What is the order of execution of filters in tableau? 1) Context 2) Traditional 3) Custom 4) Show Me
    • A. 

      1,2,3,4

    • B. 

      2,3,4,1

    • C. 

      3,1,2,4

    • D. 

      4,3,2,1

  • 23. 
    Will filters work when we do data blending?
    • A. 

      True

    • B. 

      False

  • 24. 
    Point out the correct statement:
    • A. 

      Machine learning focuses on prediction, based on known properties learned from the training data

    • B. 

      Data Cleaning focuses on prediction, based on known properties learned from the training data.

    • C. 

      Representing data in a form which both mere mortals can understand and get valuable insights is as much a science as much as it is art

    • D. 

      None of the Mentioned

  • 25. 
    Which of the following can be considered as random variable ?
    • A. 

      The outcome from the roll of a die

    • B. 

      The outcome of flip of a coin

    • C. 

      The outcome of exam

    • D. 

      All of the Mentioned