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DTA621S - DATA ANALYTICS - 2ND OPP - JAN 2024 |
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nAmI BI AunIVER s ITY
OF SCIEnCE Ano TECHnOLOGY
FACULTYOF COMPUTING AND INFORMATICS
DEPARTMENTOF INFORMATICS
QUALIFICATIONS:BACHELOR OF COMPUTER SCIENCE;BACHELOR OF INFORMATICS
QUALIFICATIONCODE:07BCMS; 07BAIT LEVEL:6
COURSECODE:DTA621S
COURSE: DATA ANALYTICS
DATE: JANUARY 2024
SESSION:1
DURATION: 3 HOURS
MARKS: 70
SUPPLEMENTARY/SECONDOPPORTUNITYEXAMINATION QUESTION PAPER
EXAMINERS:
Mrs Ruusa lpinge
MODERATOR(S):
Dr Jacob Ongala
THIS EXAMINATION PAPERCONSISTSOF 9 PAGES
(INCLUDING THIS FRONTPAGE)
INSTRUCTIONSFORTHE CANDIDATE
1. Answer all questions.
2. When writing, consider the following: The style should be to inform rather than
impress.
3. Information should be brief and accurate.
4. Please ensure that your writing is legible, neat and presentable.
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PART 1: MULTIPLE QUESTIONS (20 MARKS MAXIMUM 1 MARK FOR EACH CORRECT
ANSWER)
Answer all questions. Select ONLY ONE BEST ANSWER to each question.
1. _ is a category, also called supervised machine learning methods in which the
data is split on two parts.
a) Classification
b) Clustering
c) Data mining
d) None of the mentioned above
2. An advantage of using computer programs for qualitative data is that they_.
A Can reduce time required to analyse data.
B. Help in storing and organizing data!
C. Make many procedures available that are rarely done by hand due to time constraints.
D. All of the mentioned above
3. Logistic regression is used to find the probability of event = Success and event=
a) Failure
b) Success
c) Both A and B
d) None of the mentioned above
4. This is the process of reorganising data and cleaning data by removing
redundant and unstructured data and making the data look similar across all
records
a) Smoothing
b) Data aggregation
c) Discretization
d) Normalisation
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5. This is the type of research that It answers key questions such as "how many,
"what" and "why".
a) Quantitative
b) Qualitative
c) Nominal
d) Category
6. _ are used when we want to visually examine the relationship between two
quantitative variables.
a. Bar graph
b. Scatterplot
C. Line graph
d. Pie chart
7. A graph that uses vertical bars to represent data is called a __ .
A. Bar graph
B. Line graph
C. Scatterplot
D. All the mentioned above
8. Data Analytics uses_ to get insights from data.
a) Statistical figures
b) Numerical aspects
c) Statistical methods
d) None of the mentioned above
9. Least Square Method uses_.
a) Linear polynomial
b) Linear regression
c) Linear sequence
d) None of the mentioned above
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10. Take a look at the confusion matrix above containing 263 observations. What is the
accuracy of the predictions?
O.erl-
39
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51
Truth
A. The accuracy is equal to (165 + 51)/263 (82.1%).
B. The accuracy is equal to (165 + 8)/263 (65.8%).
C. The accuracy is equal to (51)/263 (19.4%).
D. The accuracy is equal to (39 + 8)/263 (17.9%)
11. What is Machine learning?
a) The autonomous acquisition of knowledge using manual programs.
b) The selective acquisition of knowledge using manual programs.
c) The autonomous acquisition of knowledge using computer programs.
d) The selective acquisition of knowledge using computer program.
12. Machine Learning is a field of Al consisting of learning algorithms that.___ _
a. At executing some task
b. Over time with experience
c. Improve their performance.
d. All mentioned above.
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13. Which of the following is not a supervised learning?
a. PCA
b. Naive Bayesian
c. Linear Regression
d. Decision Tree
14. Machine Learning technique that helps in detecting the outliers in data.
a) Clustering
b) Classification
c) Anomaly Detection
d) All the above
15. Which answer best describes standard deviation?
a) Standard deviation is a measure of the spread of a dataset.
b) Standard deviation indicates how much individual values vary from the mean.
c) Standard deviation helps scientists summarize how much variation there is in a
dataset or population.
d) All the above
16. If the mean score for two different datasets is the same, the standard deviation
will necessarily be the same.
a) True
b) False
17. If an experiment is repeated correctly several times, it should yield
a) a distribution of measurements around some central value.
b) a single value that is obtained each and every time.
c) widely and randomly varying results.
d) Unpredictable results
18. In Python, what is the result of the following operation '1 '+'2'
a. '2'
b. '3'
C. 3
d. '12'
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19. In Python, if you executed name= 'Lizz', what would be the output of print(name
[0:2])?
a. Lizz
b. L
C. LI
d. Liz
20. What is the output of the following lines of code:
x=1
if(x!=1):
print('Hello')
else:
print('Hi')
print('Mike')
a) Mike
b) Hello Mike
c) The Mike
d) Hi Mike
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PART 2: STRUCTURED QUESTIONS
ANSWER ALL QUESTIONS
Questions 1
1. Explain the difference between the following term
[10)
a)
Supervised and Unsupervised machine learning.
b)
Training and Test data sets
c)
Logistic and Polynomial Regression
d)
Tuple and List
e)
Variance and Standard Deviation
Question 2
a) A class contains 39 children. The following children were chosen at random, and
their weight were recorded in cm: 38, 51, 46, 79, and 57. Calculate their weight'
standard deviation.
[6]
b) Why Is Standard Deviation Often Used More Than Variance?
[2]
Question 3
1. Explain the output of the following codes written in python programming language. [1O]
a) a= 2
b = 330
print("A") if a > b else print("B")
b) Gemuse = ["apple", "banana", "cherry"]
print(len(Gemuse))
c) Gemuse1 = ("apple", "banana", "cherry")
print(type(Gemuse1 ))
d) import pandas as pd
df = pd.read_csv('data.csv')
df.fillna(130, inplace = True)
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e) i = 1
while i < 6:
print(i)
i += 1
PART 3: APPLICATION OF MACHINE LEARNING
Question 4
a) Identify and explain the types of neural network algorithm presented in the pictures
bellow
[4]
A
B
lliddenlayerI
Hiddenlayer2
Inputlayer
Outputlayer
a) Look at the following diagram of Neural Network (NN). Given input 1 and input 2 that
are independent of Input 2 and Input 3 . The output is donated by S, and the bias is 5 in
both cases.
i)
Calculate the Activation Function given the threshold below and state
what will be the output. Show your work. [7]
Threshold
0 = S > 10
1 = S::;; 10
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lnput1=3
lnput2=1
lnput3=1
Bias=5
output(S)
lnput4=0.5
PART 4: DATA PROTECTION
Question 5
Under the GDPR, organisations must meet six data protection principles whenever they process
personal data. Explain the principles of the General Data Protection Regulation (GDPR) [1 O]
END OF QUESTION PAPER
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