JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD
JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD B.Tech III INTRODUCTION TO ANALYTICS (ASSOCIATE ANALYTICS I) Previous Question Paper (February - 2023 - R16)
Note: i) Question paper consists of Part A, Part B. ii) Part A is compulsory, which carries 25 marks. In Part A, Answer all questions. iii) In Part B, Answer any one question from each unit. Each question carries 10 marks and may have a, b as sub questions.
Part A
Define R data frame. Give example.
Answer
An R data frame is a two-dimensional, tabular data structure used to store heterogeneous data, where each column can contain a different type of data (e.g., numeric, character, or logical). It is essentially a special type of list where every element is a vector of the same length.
Example:
List various data types in R.
Answer
R supports several fundamental data types used to store information. The primary data types are:
- Numeric: Represents real numbers, including both integers and decimals (e.g., 10.5, 42).
- Integer: Represents whole numbers, denoted by an 'L' suffix (e.g., 5L).
- Character: Represents text strings enclosed in quotes (e.g., "Data").
- Logical: Represents Boolean values, which can only be TRUE or FALSE.
- Complex: Represents numbers with an imaginary component (e.g., 1+4i).
- Raw: Used to hold raw bytes of data.
Name any 4 bivariate methods and its uses in statistics.
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Explain how data is summarized in R.
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Elucidate NOSQL databases.
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Compare SQL and NOSQL.
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Define a statistical model. Give examples.
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What is heteroscedasticity?
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Name the 5Vs of data analytics.
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What are the data analytics methods that could be used to predict the Gold price for the next year?
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Part B
Give an account on outliers? How are they handled with R functions? Give example.
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File handling in R
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Matrix in R.
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Elaborate on population and theoretical distributions.
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Scatter plots
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Central limit theorem.
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With code explain the process of connecting different file types and NoSQL databases to R.
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Brief on Multivalue NoSQL databases
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Handling unnormalized data in NoSQL database.
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Enumerate the types of regression. Explain them with example.
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Autocorrelation with example
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Forecasting methods.
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Explain various phases in the process of understanding a system.
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Explain requirements gathering process in detail.
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