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Gujarat Technological University

The document is an exam for a Data Analysis and Visualization course consisting of 5 questions covering various topics related to data analysis and visualization. It includes questions about inferential statistics, probability, regression, classification, clustering, time series analysis, data visualization techniques like D3.js and Tableau, and designing effective data visualizations. Students have 2 hours and 30 minutes to answer all questions, which range from 3 to 7 marks each. Simple calculators are permitted but programming is not required.

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290 views1 page

Gujarat Technological University

The document is an exam for a Data Analysis and Visualization course consisting of 5 questions covering various topics related to data analysis and visualization. It includes questions about inferential statistics, probability, regression, classification, clustering, time series analysis, data visualization techniques like D3.js and Tableau, and designing effective data visualizations. Students have 2 hours and 30 minutes to answer all questions, which range from 3 to 7 marks each. Simple calculators are permitted but programming is not required.

Uploaded by

Xxter2
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
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Seat No.: ________ Enrolment No.

___________

GUJARAT TECHNOLOGICAL UNIVERSITY


BE - SEMESTER–VI(NEW) EXAMINATION – WINTER 2022
Subject Code:3161613 Date:15-12-2022
Subject Name:Data Analysis and Visualization
Time:02:30 PM TO 05:00 PM Total Marks:70
Instructions:
1. Attempt all questions.
2. Make suitable assumptions wherever necessary.
3. Figures to the right indicate full marks.
4. Simple and non-programmable scientific calculators are allowed.
MARKS
Q.1 (a) Discuss inferential statistics in data analysis. 03
(b) Write a note on data visualization. 04
(c) Briefly discuss: linear, non-linear and multi-linear regression methods. 07
Q.2 (a) Discuss probability. 03
(b) Write a note on outliers with its detection methods. 04
(c) Explain working of k-nearest neighbor algorithm with suitable example. 07
OR
(c) Explain working of random forest algorithm. 07

Q.3 (a) Briefly discuss classification technique. 03


(b) Explain DBScan method for clustering. 04
(c) Explain working of average nearest neighbor algorithm. 07
OR
Q.3 (a) Write a note on nearest neighbor analysis. 03
(b) Write the differences between clustering and classification. 04
(c) Briefly discuss k-means clustering algorithm with its pros and cons. 07

Q.4 (a) Write a note on time series analysis. 03


(b) Briefly discuss use of D3.js for data visualization with its pros and cons. 04
(c) Write a note on big three principles of data visualization. 07
OR
Q.4 (a) Discuss: “how to pick the most appropriate design style in data 03
visualization”.
(b) Briefly discuss comparative graphics. 04
(c) Write a note on D3-DOM selection methods with appropriate examples. 07

Q.5 (a) Write a note on “Plotly” for data visualization. 03


(b) Explain analyzing spatial data 04
(c) Explain HTML and DOM in Data Visualization with the help of 07
appropriate example.
OR
Q.5 (a) Write a note on “Tableau Public”. 03
(b) Explain popular web analytics applications used by data scientist. 04
(c) Discuss various points to design dashboard for data visualization. 07

*************

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