Question Paper Code : 30118
B.E./B.Tech. DEGREE EXAMINATIONS, APRIL/MAY 2023.
Third Semester
Computer Science and Engineering
CS 3352 — FOUNDATIONS OF DATA SCIENCE
(Common to : Computer Science and Engineering (Artificial Intelligence and Machine Learning)/Computer Science and Engineering (Cyber Security)/Computer and Communication Engineering/Electronics and Instrumentation Engineering/Instrumentation and Control Engineering/Information Technology)
(Regulations 2021)
Answer ALL questions.
PART A — (10 × 2 = 20 marks)
- 1.
Outline the difference between structured data and unstructured data.
- 2.
Define data mining.
- 3.
Compare and contrast qualitative data and quantitative data with an example.
- 4.
List the differences between a discrete variable and a continuous variable with an example.
- 5.
What is the use of scatter plot?
- 6.
Define correlation coefficient.
- 7.
State the advantages of using Numpy arrays.
- 8.
Outline the two types of Numpy's UFuncs.
- 9.
State the two possible options in IPython notebook used to embed graphics directly in the notebook.
- 10.
How plt.scatter function differs from plt.flot function?
PART B — (5 × 13 = 65 marks)
- 11.(a)
Elaborate about the steps in the data science process with a diagram.
- Or
- (b)
What is a data warehouse? Outline the architecture of a data warehouse with a diagram.
- 12.(a)
- (i)What is a frequency distribution? Customers who have purchased a particular product rated the usability of the product on a 10-point scale, ranging from 1 (poor) to 10 (excellent) as follows: [3 7 2 7 8; 3 1 4 10 3; 2 5 3 5 8; 9 7 6 3 7; 8 9 7 3 6] Construct a frequency distribution for the above data.(5)
- (ii)What is relative frequency distribution? The GRE scores for a group of graduate school applicants are distributed as follows: [Table: GRE Score, Frequency: 725-749, 1; 700-724, 3; 675-699, 14; 650-774, 30; 625-649, 34; 600-624, 42; 575-599, 30; 550-574, 27; 525-549, 13; 500-524, 4; 475-499, 2; Total, 200] Explain the procedure to convert a frequency distribution into a relative frequency distribution and convert the data presented in the above table to a relative frequency distribution. Do not round numbers to two digits to the right of the decimal point.(8)
- Or
- (b)
- (i)What is Z-score? Outline the steps to obtain a Z-score.(7)
- (ii)Express each of the following scores as a Z score: First, Mary's intelligence quotient is 135, given a mean of 100 and standard deviation 15. Second, Mary obtained a score of 470 in the Competitive Examination conducted in April 2022, given a mean of 500 and a standard deviation of 100.(6)
- 13.(a)
Calculate the correlation coefficient for the heights 'in inches' of fathers' (x) and their son's (y) with the data presented below. [x: 66, 68, 68, 70, 71, 72, 72; y: 68, 70, 69, 72, 72, 72, 74]
- Or
- (b)
The values of x and their corresponding values of y are presented below. [x: 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5; y: 2.5, 3.5, 5.5, 4.5, 6.5, 8.5, 10.5]
- (i)Find the least square regression line y = ax + b(9)
- (ii)Estimate the value of y when x = 10.(4)
- 14.(a)
What is an aggregate function? Elaborate about the aggregate functions in Numpy.
- Or
- (b)
- (i)What is broadcasting? Explain the rules of broadcasting with an example.(7)
- (ii)Elaborate about the mapping between Python operators and Pandas methods.(6)
- 15.(a)
Explain about various visualization charts like line plots, scatter plots and histograms using Matplotlib with an example.
- Or
- (b)
Outline any two three-dimensional plotting in Matplotlib with an example.
PART C — (1 × 15 = 15 marks)
- 16.(a)
- (i)What is mode? Can there be distributions with no mode or more than one mode? The owner of a new car conducts six gas mileage tests and obtains the following results, expressed in miles per gallon: 26.3, 28.7, 27.4, 26.6. 27.4, 26.9. Find the mode for these data.(5)
- (ii)What is median? Outline the steps to find the median and find the median for the following scores: first, set of five scores 2, 8,2,7,6 and second, set of six scores 3,8,9,3, 1,8 with steps.(10)
- Or
- (b)
Consider the following dataset with one response variable y and two predictor variables x1 and x2. [y: 140, 155, 159, 179, 192, 200, 212, 215; x1: 60, 62, 67, 70, 71, 72, 75, 78; x2: 22, 25, 24, 20, 15, 14, 14, 11] Fit a multiple linear regression model to this dataset.