Big Data
1. Who popularized Big Data term?
a) John
Deere b) John Mashed
C)
Johnny Masha d)
John Mash
Answer: b) John Mashed
2. Numbers, text, image, audio, and video data is
a)
Volume b) value
c)
Verity d) Variety
Answer : d) Variety
3. Real time data is
a)
fields b)
primary key
c)
unique d) record
Answer : c) unique
4. ……….. is a term that is used to describe data that is
high volume, high velocity, and/ or high variety.
a)
Analytics b) Big
Data
c)
Hadoop data d) Big data
analytics
Answer : b) Big Data
5. ………. Digital data is based on Relational database table.
a)
Structured b)
Unstructured
c)
Semi-structured d) Semi-
Unstructured
Answer : a) Structured
6. …….. digital data is based on XML/RDF.
a)
Structured b)
Unstructured
c)
Semi-structured d) Semi-
Unstructured
Answer : b) Unstructured
7. ……. Digital data is based on character and binary data.
a)
Structured b)
Unstructured
c)
Semi-structured d) Semi-
Unstructured
Answer : c) Semi-structured
8. …….. is not processing source of Big Data.
a) R b)
Yahoo! Pipes,
c)
Mechanical Turk d) Data meter
Answer: d) Data meter
9. ……. Is concerned with extraction of actionable knowledge
and insights from big data.
a) Data
analytics b) Big Data
c)
Digital data d)
Descriptive Analytics
Answer : a) data analytics
10. ……. Essentially tells what happened in the past and
presents it in an easily understandable form.
a) Data
analytics b) Big Data
c)
Digital data d) Descriptive Analytics
Answer : d) Descriptive Analytics
11. ……….. extrapolates from available data and tells what is
expected to happen in the near future.
a)
Predictive Analytics b) Big data
c)
Digital data d)
Descriptive Analytics
Answer : a) Predictive Analytics
12. ………. Finds unexpected relationships among parameters is
collections of big data.
a)
exploratory or discovery Analytics b)
Predictive Analytics
c)
Digital data d)
Descriptive Analytics
Answer : a)
exploratory or discovery Analytics
13. ……….. useful knowledge from data to solve business
problems can be treated systematically by following a process with reasonably
well-defined stages.
a) Extracting b) Preparing
c) Prescribing d) None
Answer : a) Extracting
14. ………. Answers the question “What has happed?”
a)
Descriptive analytics b)
predictive analytics
c)
Prescriptive analytics d)
None
Answer : a) Descriptive analytics.
15. ………….. answer the question “What will happen?”
a)
Descriptive analytics b)
predictive analytics
c)
Prescriptive analytics d)
None
Answer : b) predictive analytics
16. ………….. answer the question “How can we make it happen?”
a)
Descriptive analytics b)
predictive analytics
c)
Prescriptive analytics d)
None
Answer : c) Prescriptive analytics
17. …… is most
important language for Data Science.
a) Java b) Ruby
c) R d) None of the
mentioned.
Answer : c) R
18. ……… phase of the data analytics lifecycle usually
takes the longest time.
a)
Phase 2 : Data preparation b) Phase 3
: Model Planning
c)
Phase 4 : Model Building d) Phase
5 : communicate Results
Answer : a) Phase 2 : Data preparation
19. When data are collected in a statistical study for only
a portion or subset of all elements of interest we are using.
a)
Sample b) Parameter
c)
Population d) None
Answer : a) Sample
20. In Statistics, a population consists of
a) All
People living in a country.
b) All
people living in the city are under study.
c) All
subjects or objects whose characteristics are being studied.
d) None
of the above
Answer : c) All subjects or objects whose characteristics
are being studied.
21. The strength (degree) of the correlation between a set
of independent variables X and a dependent variable Y is measure by
a)
Coefficient of Correlation b)
Coefficient of Determination
c)
Standard error of estimate d) All of
the above.
Answer : a) Coefficient of Correlation
22. Correlation coefficient values lies between
a) -1
and +1 b) 0 and 1
c) -1
and 0 d) None of these
Answer : a) -1 and +1
23. In correlation, both variables are always
a)
Random b) Non Random
c) Same d) None
Answer : a) Random
24. If two variables oppose each other then the correlation
will be
a)
Positive Correlation b) Zero Correlation
c)
Perfect Correlation d) Negative
Correlation
Answer : d) Negative Correlation.
25. A perfect negative correlation is signified by
a) 0 b) 1
c) 0.5 d) -1
Answer: d) -1
26. If X and Y are independent to each other, the
coefficient of correlation
a) -1 b) 0
c) +1 d) None
Answer : a) -1
27. If the scatter diagram is drawn the scatter pints lie on
a straight line then it indicate
a)
Regression b) Skewness
c) No
correlation d) Perfect
correction
Answer : c) No correlation
28. …………. Is the major assumption in a linear regression
model.
a) The
independent variables are numeric variables.
b)
There is only one dependent variable.
c) The
relationship between the independent and dependent variables is linear.
d) The
error term is a normally distributed random variable with mean zero and
constant variance.
Answer : c) The relationship between the independent and
dependent variables is linear.
29. ……… input (independent) variables are in used a simple
linear regression model.
a) 1 b) 2
c) 3 d) depends on the number of
features/attributes involved Bottom of Form.
Answer: a) 1
30. …….. of the following is not a step in data analysis.
a) Obtain the data b)
Clean the data
c) EDA d)
None of the mentioned
Answer : d) None of the mentioned
31. Regression analysis ………
a)
Establishes a relationship between two variables. B) Establishes cause and effect.
c)
Measures growth. D)
Measures the demand for a good.
Answer: a) Establishes a relationship between two variables.
32. The dependent variable is also called…..
a)
Regression b) Regress
and
c)
Continuous variable d) Independent
Answer: b) Regress and
33. The independent variable is also called…………
a) Regressor b) Predict and variable
c) Explained Variable d) All of these
Answer : a) Regressor
34. ………… is about
developing code to enable the machine to learn to perform tasks and its basic
principle is the automatic modeling of underlying processes that have generated
the collected data.
a) Data Science b) Machine
learning (ML)
c) Data
analytics d) All of the
Mentioned
Answer : b) Machine learning (ML)
35. Groups of related observations are called …………….. and
the procedure to organize items of a given collection into groups base on some
similar features called as………………
a)
clusters, analysis b)
regression, clustering
c)
cluster, clustering d)
None of the Mentioned
Answer : c) cluster, clustering
36. ……… rule mining is a technique to identify underlying
relations between different items.
a)
Association b) analytics
c)
Learning d) All of the Mentioned.
Answer : a) Association
37. ………… is a form of supervised learning. Mail service
provider like Gmail, Yahoo and other use this technique to classify a new mail
as spam or not spam.
a)
Machine Learning b) Classification
c)
Regression d) All of
the mentioned
Answer : b) Classification
38. Examples of supervised learning includes………….
a)
Regression b) Decision
Tree
c) KNN d) All of the
Mentioned
Answer: d) All of the Mentioned
39. A Naive Bayes Classifier is a ……….. machine learning algorithm which relies
on the assumption of feature independent to classify input data.
a) supervised b) Unsupervised
c) semi-supervised d) All of the Mentioned
Answer : a) supervised
40. …………….. analysis
has become one of the most widely used statistical tools for analyzing
multifactor data and it is appealing because it provides a conceptually simple
method for investigating functional relationships among variables.
a)
Clustering b)
Regression
c) Data d) All of the
Mentioned
Answer : b) Regression
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