BA02 Advanced Analytics Using R Assignment 2

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Question 1:- Which of these is not a dimension of data quality?

a)         Timeliness                       

b)         Completeness                       

c)         Continuity                       

d)         Consistency                       

Question 2:- While implementing k-means algorithm for clustering analysis, which of the following is the correct way of initializing the clustering process?

a)         Randomly choose k units from the dataset as the initial cluster means                       

b)         Calculate the distances between the clusters.                       

c)         Generate the dendrogram for the clusters.                       

d)         Find the total number of objects.                       

Question 3:- Which of the following is a mandatory step to estimate n number of β coefficients for a regression model?

a)         Take the partial derivative with respect to each β coefficient                       

b)         Equate all independent variables to 0                       

c)         Equate each β coefficient to 0                       

d)         Take the partial derivative with respect to each independent variable                       

Question 4:- Suppose a logistic regression model is formulated with three variables: D, X1, X2. The D variable is dependent on X1 and X2. The X1 and X2 variables also have some kind of interaction that affects the value of a.

Which of the following term will you add in the equation to include the interaction between X1 and X2? a)           X1+x2                       

b)         X1*X2                       

c)         X1/X2                       

d)         X1*X1+X2*X2                       

Question 5:- Which of these is an activity a data warehouse should be able to do? a)           Organize data                       

b)         Manipulate data                       

c)         Integrate data                       

d)         All of the above                       

Question 6:- In model selection and fitting for forecasting, what is fitting?

a)         Estimating the known model parameters, usually by the method of least squares.                       

b)         Estimating the unknown model parameters, usually by the method of least squares.                       


  Estimating the unknown model parameters, usually by the method of highest squares                       

  None of the above                       

Question 7:- Which of these forecasting techniques are subjective in nature?



  Both a and b                       

  1. None of the above

Question 8:- In which of these areas is forecasting primarily important?




  All of the above                       

Question 9:- The a priori property states that if an itemset Z is not frequent, then adding another item A to the itemset Z will not make Z more frequent



  May be either a or b                       

  Not coming in preview of apriority property rules                       

Question 10:- Which of these can the generalized rule induction (GRI) handle as inputs?

  Categorical variable                       

  Numerical variable                       

  Both a and b                       

  None of the above                       

Question 11:- A model may be descriptive or inferential.



  All models are statistical                       

  None of the above                       

Question 12:- Which of these best define a model?

  A global description or explanation of a data set, taking a high level perspective.                       

  Local features of the data                       

  Insight drawn from a series of data                       

  Visualization of data related to various categories                       

Question 13:- Association rule mining can be applied either in a supervised or an unsupervised manner. 1 True , 2



  Both a and b                       

  Unsupervised variable is applied on No target variable                       


Question 14:- The two main categories of DB engines used in the Operational Databases layer of the Big Data stack are:

a)         Columnar and key-value pair                       

b)         RDBMS and NoSQL                       

c)         Columnar and document databases                       

d)         Risk and MongoDB                       

Question 15:- ETL tools are a part of which layer of the Big Data technology stack? a)           Application Layer                       

b)         Network Layer                       

c)         Security Layer                       

d)         Organizing data services and tools layer                       

Question 16:- Which of the following is a Big Data application used for log data analysis? a)           Dataxu                       

b)         Bluefin                       

c)         Splunk                       

d)         Myrrix                       

Question 17:- Which of these services/tools is needed for the loading and conversion of Data? a)           Distributed Files System                       

b)         Extract, transform, and load (ETL)                       

c)         Workflow services                       

d)         All of the above                       

Question 18:- Which of these method is a way to identify outliers for numeric variables? a)           Histograms                       

b)         Scatter plots                       

c)         Both a and b                       

d)         None of the above                       

Question 19:- Removal of which of these is a key reason to pre-process data? a)           Missing values                       

b)         Outliers                       

c)         Redundant fields                       

d)         All of the above                       

Question 20:- Which of these is NOT a key concept in time series analysis? a)           Trend                       

b)         Volume                       

c)         Serial dependence                       

d)         Stationary                       




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