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WorksheetsD@+a
Total questions: 75
Worksheet time: 1hrs 29mins
What is data?
Unprocessed infomation
Set of values
Ideas or objects
All of the choices
What is Big Data?
Data with a large size
Data with the word 'big' in it
Data about people who are big
Data made with a big purpose
What are the 3 main concepts of Data Science?
Data, Science, and Knowledge
Mathematics, Computer Science, and Domain Expertise
Machine Learning, Data Processing, and Statistical Research
What is Data Science comprised of?
Predictive
Machine Learning
Business Intelligence
Personal Opinion
Can be described as huge amount of data
Volume
Variety
Value
Velocity
Veracity
Can be described as different formats of data from various sources
Volume
Value
Veracity
Variety
Velocity
Can be described with extracting useful data
Volume
Value
Veracity
Variety
Velocity
Can be described as the high speed of accumulation of data
Volume
Variety
Value
Velocity
Veracity
Can be described as inconsistencies and uncertainty in data
Volume
Value
Veracity
Variety
Velocity
The process of evaluating data through analytical and statistical tools
Data Mining
Data Analysis
Data Exploration
Data Visualization
Which was not mentioned as a latest trend tool
SPSS
Excel
Pentaho
Notepad
Which of the following is performed by Data Scientist ?
Define the question
Create reproducible code
Challenge results
All of the Mentioned
Which of the following is most important language for Data Science ?
Java
Ruby
R
None of the mentioned
Which of the following approach should be used to ask Data Analysis question ?
Find only one solution for particular problem
Find out the question which is to be answered
Find out answer from dataset without asking question
None of the mentioned
Which of the following is one of the key data science skill ?
Statistics
Machine Learning
Data Visualization
All of the Mentioned
Which of the following is key characteristic of hacker ?
Afraid to say they don’t know the answer
Willing to find answers on their own
Not Willing to find answers on their own
All of the mentioned
Point out the correct statement:
Raw data is original source of data
Preprocessed data is original source of data
Raw data is the data obtained after processing steps
None of the Mentioned
Which of the following is the top most important thing in data science ?
answer
question
data
none of the Mentioned
Which of the following term is appropriate to the above figure ?
Large Data
Big Data
Dark Data
None of the mentioned
Which of the following characteristic of big data is relatively more concerned to data science ?
Velocity
Variety
Volume
None of the Mentioned
Which of the following step is performed by data scientist after acquiring the data ?
Data Integration
Data Replication
Data Cleansing
All of the Mentioned
Which of the following is the most accurate definition of data science?
a) Data science is extracting meaning from large data sets in order to provide insights to support decision-making
b) Data science is using computers to analyse data and to perform calculations on the data to produce information
c) Data science is performing experiments and recording the data produced by those experiments
d) Data science is writing code to make sure that any inaccuracies in data sets are spotted and removed (cleaned)
Which of the following best describes a data visualisation?
A. Presenting related data so that a user can see individual items of data
B. Making sure that data is accessible and that no data is hidden
C. A visual representation that communicates relationships among the data
D. A collection of graphs that tell a story when put together
Is the following a visualisation or an infographic?
A. Visualisation
B. Infographic
What is meant by a correlation?
A. The relationship between two or more variables
B. When there is an upward trend in a graph
C. When there is a set of data that doesn’t lie in the normal or expected range
D. When data is placed in a graph
The visualisation below plots life expectancy (y-axis) against time (x-axis). What type of correlation does this visualisation show from 1949 onwards?
A. Positive
B. Negative
C. Neutral
D. No correlation is visible
The following graph shows the annual average temperatures recorded by a weather station over a period of 20 years. Identify the outlier in the data.
A. Point A
B. Point B
C. Point C
D. Point D
Which of the following is the correct order of the investigative cycle?
A. Problem, data, plan, analysis, conclusion
B. Conclusion, plan, problem, data, Analysis
C. Plan, problem, analysis, data, conclusion
D. Problem, plan, data, analysis, conclusion
In which step of the cycle would you pose the question(s) that you will use data to help you answer?
A. Data
B. Analysis
C. Plan
D. Problem
In which step of the cycle would you cleanse the data?
A. Data
B. Analysis
C. Plan
D. Problem
In which step of the cycle would you work out where the data will come from or how you will collect it?
A. Data
B. Analysis
C. Plan
D. Problem
How many students spent 7 hours doing homework that week?(1 mark)
6
5
7
4
How many total students are represented by the histogram?(1 mark)
32
31
35
8
What is the MEDIAN of this data?(1 mark)
95
90
100
40
What was the difference between the cars sold on Monday and Tuesday than the cars sold on Friday and Saturday? (1 mark)
4
3
2
1
What is name of the chart pictured below? (1 mark)
Graph chart
Pie chart
Line chart
Bar chart
What is name of the chart pictured below? (1 mark)
Graph chart
Pie chart
Line chart
Bar chart
What is name of the chart pictured below? (1 mark)
Graph chart
Pie chart
Line chart
Bar chart
What is Machine Learning? (Choose 3 Answers)
Artificial Intelligence
Machine Learning
Data Statistics
Deep Learning
Which one in the following is not Machine Learning disciplines?
Information Theory
Neurostatistics
Optimization + Control
Physics
from the picture, what kind of programming is it?
Traditional Programming
Modern Programming
Machine Learning
Traditional Learning
from the picture, what kind of programming is it?
Traditional Programming
Machine Learning
Modern Programming
Traditional Learning
What kind of learning algorithm for "Future stock prices or currency exchange rates"?
Recognizing Anomalies
Prediction
Generating Patterns
Recognition Patterns
What kind of learning algorithm for "Facial identities or facial expressions"?
Recognizing Anomalies
Prediction
Generating Patterns
Recognition Patterns
Which of the following is not type of learning?
Semi-unsupervised Learning
Unsupervised Learning
Supervised Learning
Reinforcement Learning
Real-Time decisions, Game AI, Learning Tasks, Skill Aquisition, and Robot Navigation are applications in ...
Unsupervised Learning: Clustering
Supervised Learning: Classification
Reinforcement Learning
Unsupervised Learning: Regression
Targetted marketing, Recommended Systems, and Customer Segmentation are applications in ...
Unsupervised Learning: Clustering
Supervised Learning: Classification
Reinforcement Learning
Unsupervised Learning: Regression
Fraud Detection, Image Classification, Diagnostic, and Customer Retention are applications in ...
Unsupervised Learning: Clustering
Supervised Learning: Classification
Reinforcement Learning
Unsupervised Learning: Regression
This picture shows a result of ...
Supervised Learning: Classification
Unsupervised Learning: Regression
Unsupervised Learning: Prediction
Supervised Learning: Regression
This picture shows an application of ...
Supervised Learning: Classification
Unsupervised Learning: Clustering
Unsupervised Learning: Prediction
Supervised Learning: Regression
Machine Learning has various function representation, which of the following is not function of symbolic?
Decision Trees
Rules in propotional Logic
Hidden-Markov Models (HMM)
Rules in first-order predicate logic
Machine Learning has various function representation, which of the following is not numerical functions?
Linear Regression
Support Vector Machines
Neural Network
Case-based
Machine Learning has various search/ optimization algorithms, which of the following is not evolutionary computation?
Perceptron
Genetic Algorithm (GA)
Neuro Evolution
Genetic Programming (GP)
What type of Machine Learning Algorithm is suitable for predicting the continuous dependent variable?
Logistic Regression
Linear Regression
Decision Tree Classifier
KNN Classifier
What type of Machine Learning Algorithm is suitable for predicting the dependent variable with two different values?
Logistic Regression
Linear Regression
Multiple Linear Regression
Polynomial Regression
The correlation in between mobile usage and exam score of a person found to be -2.2. What is your inference from the above statement.
Mobile usage is positively correlated with exam score
Mobile usage is negatively correlated with exam score
None of the mentioned
Need some other information
The residual is the difference in between ________________
actual value of y and the estimated value of y
actual value of x and the estimated value of x
actual value of y and the estimated value of x
actual value of x and the estimated value of y
Suitable evaluation metric for measuring the performance of a given regression model is
Mean Absolute Error
Root Mean Square Error
Precision
Recall
If we decrease the input variable by one unit in a simple linear regression model. How many units of the output variable will change?
reduced by Intercept
increased by Intercept
increased by Slope
reduced by Slope
Appropriate chart for visualizing the linear relationship between two variables is _________________
Scatter plot
Barchart
Histograms
None of Mentioned
The Number of coefficients required to estimate a simple linear regression?
1
2
0
3
KNN Algorithm can be used for
Only for Classification
Only for Regression
Both Classification and Regression
None of the Mentioned
KNN is ___________ algorithm
Non-parametric and Lazy Learning
Parametric and Lazy Learning
Parametric and Eager Learning
Non-parametric and Eager Learning
What kind of distance metric(s) are suitable for categorical variables to finding the closest neighbors
Euclidean Distance
Manhattan distance
Minkowski distance
Hamming distance
What kind of distance metric(s) are suitable for continuous variables to find the closest neighbors
Euclidean Distance
Manhattan distance
Minkowski distance
Hamming distance
KNN algorithm appropriate for
Lower number of features
Large number of features
No such restriction on number of features
None of the Mentioned
KNN algorithm requires
More time for training
More time for testing
Equal time for training and testing
None of the Mentioned
The entropy of a given dataset is zero. This statement implies what?
further splitting is required
no further splitting is required
Need some other information to decide splitting
None of the Mentioned
If the given dataset contains 100 observations out of 50 belongs to class1 and other 50 belongs to class2. What will be the entropy of the given dataset?
0
1
-1
0.5
How do you choose the root node while constructing a Decision Tree?
An attribute having high entropy
An attribute having largest information gain
An attribute having high entropy and Information gain
None of the Mentioned
Chose the correct criterion for Decision Tree Classifier in sklearn package
Gini
Entropy
Information Gain
Random
In a Decision Tree Leaf Node represents_____________
One of the Class Label
One of the complete observation
One of the attribute
None of the Mentioned
Consider the above Confusion Matrix of a classifier and choose the correct statements
Accuracy is 84%
Misclassification Rate is 16%
Type-I Error is 6
Type-II Error is 10
Artificial Intelligence is superset of ________________________ & ________________________ ,
Machine Learning & Neural Networks
Machine Learning & Deep Learning
Deep Learning & Neural Networks
Machine Learning is a subset of AI. ML deals with developing systems which can improve their performance with _________________.
Experience
Deep Learning
Neural Networks
