Dell EMC Data Science and BigData Certification Questions and Answers

Question : You are analyzing a time series and want to determine its stationarity. You also want to determine
the order of autoregressive models.
How are the autocorrelation functions used?


1. PACF as an indication of stationarity, and ACF for the correlation between Xt and Xt-k not
explained by their mutual correlation with X1 through Xk-1.
2. ACF as an indication of stationarity, and PACF to determine the correlation of X1 through Xk-1.
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4. ACF as an indication of stationarity, and PACF for the correlation between Xt and Xt-k not
explained by their mutual correlation with X1 through Xk-1.


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Explanation: Autocorrelation is the linear dependence of a variable with itself at two points in time. For stationary processes, autocorrelation between any two observations only depends on the time lag h
between them. Define Cov(yt, yt-h) = Yh. The autocorrelation function tells us the time interval over which a correlation in the
noise exists. If the noise is made entirely of waves, and the waves move through the plasma (or other medium) without decaying as they travel, the autocorrelation
will be large for all time. Why does the autocorrelation Why does the autocorrelation decay in time ? decay in time ? because the data does not go on forever.
Autocorrelation, also known as serial correlation or cross-autocorrelation, is the cross-correlation of a signal with itself at different points in time (that is what the cross stands for). Informally, it is the
similarity between observations as a function of the time lag between them. It is a mathematical tool for finding repeating patterns, such as the presence of a periodic signal obscured by noise, or identifying the
missing fundamental frequency in a signal implied by its harmonic frequencies. It is often used in signal processing for analyzing functions or series of values, such as time domain signals.






Question : Which word or phrase completes the statement? A spreadsheet is to a data island as a centralized
database for reporting is to a ________?


1. Data Repository
2. Analytic Sandbox
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4. Data Warehouse

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Explanation: Excel Spreadsheets are frequently used in Data Warehousing applications to access and present data from Data Marts. Spreadsheets are powerful, flexible and relatively inexpensive tools that many decision makers
are comfortable using.

Before Data Warehousing became popular, decision makers often had difficulty getting access to corporate data. It was necessary to populate spreadsheets from multiple disparate data sources and manually integrate the
data. This process was both time consuming and error-prone.

Privacy, data redundancy and currency issues arose when decision makers retained their own personal copies of sensitive corporate data on the personal computers and laptops.






Question : Which R data structure allows elements to have different data types?


1. Matrix
2. Vector
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4. Array

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Explanation: Lists ("generic vectors") are another kind of data storage. Lists have elements, each of which can contain any type of R object, i.e. the elements of a list do not have to be of the same type.
List elements are accessed through three different indexing operations. These are explained in detail in Indexing.

Lists are vectors, and the basic vector types are referred to as atomic vectors where it is necessary to exclude lists.

Related Questions

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Question : You are working as a data science consultant for a gaming company. You have three member team and all other stake holders are from the company itself like project managers and project sponsored, data team
etc. During the discussion project managed asked you that when can you tell me that the model you are using is robust enough, after which step you can consider answer for this question?


1. Data Preparation

2. Discovery

3. Operationalize

4. Model planning

5. Model building



Question : Which of the following statements are correct with regards to R programming vector?
A. Vector always have character types internally
B. Vector is having one dimension.
C. Vector elements are always with the same data types.
D. Vector (1,2,3,"four",TRUE) internally store this value as "1" "2" "3" "four" "TRUE"


1. A,B
2. B,C
3. C,D
4. A,D
5. B,D


Question : Which of the following statement is true with regards to Array and List?



1. Array can have mixed data type values while List cannot.

2. List can have mixed data type values while Array cannot.

3. Both List and Array can have mixed data types.

4. Both List and Array can have only same data types.



Question : Which of the following statement is correct with regards to factor data type in R?
A. Factor can be used to represent categorical data.
B. Factors can be ordered and unordered
C. Factors are integers
D. Factors can have any undefined new value in it.
E. Factors are characters


1. A,B,C
2. B,C,D
3. C,D,E
4. A,D,E
5. A,C,E


Question : You are working as a data scientists for a company which sale the car tyre in a country. Initially you have been given a data set with almost , rows. To apply your analytics you need location
information as well and you are provided with the 25,000 records with the location information which has 150 unique cities in that. Which of the following data structure from the R programming language best fit for
this column?


1. List

2. Array

3. Vector

4. Factor



Question : Which of the following are example of qualitative data?
A. Labels
B. Softness of a cloth
C. Interval
D. Ratio


1. A,B
2. B,C
3. C,D
4. A,D
5. B,D