AL-603-B Data and Visual Analytics - May 2023 Question Paper

Under each question, How to answer lists the points an answer should cover, outlined by CampusPrep from the syllabus. Check the details against your textbook.

1. 7 Marks
   aExplain about Data Management and Indexing.
   How to answer

   • Define data management and its objectives
   • Explain indexing concept and need
   • Types of indexing and working steps
   • Applications / advantages in analytics
2. 7 Marks
   bWhat do you mean by measures of Central Tendency? Explain.
   How to answer

   • Define central tendency
   • List mean, median, mode
   • Formulas and calculation steps
   • Use and interpretation with example
3. 7 Marks
   aDefine Variables and discuss about data categorization.
   How to answer

   • Define variable and types
   • Explain data categorization levels
   • Examples of categorical vs numerical data
   • Importance in analytics
4. 7 Marks
   bHow do you calculate Chi-Square test? Explain with an example.
   How to answer

   • State Chi-Square test purpose and formula
   • Steps: observed vs expected, degrees of freedom
   • Worked example calculation
   • Interpretation of result
5. 7 Marks
   aExplain different types of variables used in Regression Modeling.
   How to answer

   • Define dependent and independent variables
   • Types: continuous, categorical, dummy, control variables
   • Role in regression modeling
   • Examples
6. 7 Marks
   bDiscuss in detail about Maximum likelihood test with an example.
   How to answer

   • Define maximum likelihood estimation concept
   • Likelihood function and maximization steps
   • Illustrative example
   • Applications and advantages
7. 7 Marks
   aWhat do you understand by Multivariate Exploration of Data? Explain.
   How to answer

   • Define multivariate exploration
   • Techniques: correlation, scatter matrix, PCA
   • Visualization methods
   • Interpretation for analytics
8. 7 Marks
   bBriefly discuss about Univariate Exploration of data.
   How to answer

   • Define univariate exploration
   • Summary statistics and distributions
   • Plots: histogram, boxplot, bar chart
   • Example interpretation
9. 7 Marks
   aExplain in detail about HDFS.
   How to answer

   • Define HDFS and Hadoop context
   • Architecture: NameNode, DataNode, blocks
   • Data read/write workflow
   • Features: fault tolerance, scalability
10. 7 Marks
    bDiscuss in detail about Data Wrangling.
    How to answer

    • Define data wrangling and need
    • Steps: cleaning, transforming, enriching
    • Tools and techniques
    • Example workflow
11. 7 Marks
    aWhat do you understand by Data Analyst Ecosystem? Explain.
    How to answer

    • Define data analyst ecosystem
    • Components: data sources, tools, platforms
    • Role of analyst in workflow
    • Example ecosystem diagram
12. 7 Marks
    bExplain different types of File Format.
    How to answer

    • Define file format and need
    • Types: CSV, JSON, Parquet, Avro, ORC
    • Comparison of features and use cases
    • Selection criteria
13. 7 Marks
    aHow to create your Own Visualization of a complex data set? Explain.
    How to answer

    • Steps for visualizing complex dataset
    • Choosing charts and tools
    • Design principles and interactivity
    • Example creation workflow
14. 7 Marks
    bBriefly discuss about Pandas in Python.
    How to answer

    • Define Pandas and its role in Python
    • Key structures: Series, DataFrame
    • Common operations for analysis
    • Example usage
15. 14 Marks
    Write short notes on any Two:

    1. a)ggplot
    2. b)Re-Sampling
    3. c)T-test
    4. d)Hive
    How to answer

    • Define the selected term and purpose
    • Key features / steps / formula
    • Example or use case
    • Advantages / applications