Data Warehousing (ZG515)
Mid-Semester Question Paper - 2016-2017 Regular
BITS PILANI WILP
Usability Engineering - ZG547- Mid-Semester Test Questionpaper 2016-17 BITS PILANI WILP
Usability Engineering - ZG547
Mid-Semester Test Questionpaper 2016-17
BITS PILANI- WILP
Usability Engineering - SSZG547 - Mid-Semester Question Paper - 2016-2017 Regular BITS PILANI WILP
Usability Engineering (SSZG547)
Mid-Semester Question Paper - 2016-2017 Regular
BITS PILANI WILP
Data Mining - ISZC415 - Mid-Semester Question Paper - 2016-2017 Regular BITS PILANI WILP
Data Mining (ISZC415)
Mid-Semester Question Paper - 2016-2017 Regular
BITS PILANI WILP
Machine Learning -ISZC464 - Mid-Semester Question Paper - 2016-2017 Regular BITS PILANI WILP
Machine Learning (ISZC464)
Mid-Semester Question Paper - 2016-2017 Regular
BITS PILANI WILP
INFORMATION RETRIEVAL - SSZG537 - Mid-Semester Question Paper - 2016-2017 Regular BITS PILANI WILP
INFORMATION RETRIEVAL - SSZG537 -
Mid-Semester Question Paper - 2016-2017 Regular
BITS PILANI WILP
Usability Engineering SSZG547 Quiz 1 - BITS PILANI WILP
Usability Engineering SSZG547 Quiz 1
BITS PILANI WILP 2017
Select one or more:
a. Hiding unwanted things
b. Disabling/enabling based on the context
c. None of the Answers
d. No hiding at all
Ans: a. Hiding unwanted things
b. Disabling/enabling based on the context
2. Wireframes are nothing but
Select one:
a. Software Code
b. Prototypes
c. None of the Answers
d. Sketches
e. Aluminum Wire
Ans: d. Sketches
3. When users encounter a coupon/promo code field on the checkout page of an ecommerce website. Even though they may not have planned to use a coupon, the very presence of a coupon box makes users to leave the checkout flow and search for a promo/coupon code: FOMO (fear of missing out) is the cause of many a lost sale on sites with prominent coupon-code fields. This phenomenon is known as:
Select one:
a. Priming
b. Muller-Lyer illusion
c. McGurk effect
d. Attentional Blink
Ans: a. Priming
4. Identify the gestalt principles in the below diagram.
Select one:
a. Common fate, similarity, Continuity
b. Symmetry, Proximity, Common fate
c. Closure, Symmetry, Common fate
d. Symmetry, Continuity, Closure
Ans: d. Symmetry, Continuity, Closure
5. Hiding & unhiding, disabling & enabling of the UI options to make the decision making more easier for the user is known as:
Select one:
a. None of the Answers
b. Principle of Progressive disclosure
c. Principle of disability
d. Principle of hide and seek
Ans: b. Principle of Progressive disclosure
6. visual perception is biased by
Select one:
a. experience
b. Both experience and current context
c. current context
d. None of the Answers
Ans: b. Both experience and current context
7. “Party effect” is an example for
Select one:
a. Perception biased by Experience
b. Perception biased by Context
c. Perception biased by Habit
d. Perception biased by Goals
Ans: d. Perception biased by Goals
8. Does visual perception gets biased by the direction?
Select one:
a. No
b. Yes
c. None of the Answers
Ans: b. Yes
9. The representation of how a machine or an application works is called as
Select one or more:
a. System model
b. Mental model
c. Implementation model
d. Conceptual model
e. Represented model
Ans: a. System model
c. Implementation model
10. User-interface design guidelines are based on?
Select one:
a. Physiology
b. Psychology
c. Psychoscopy
d. Psychometry
Ans: b. Psychology
11. The amount of time to make a decision in a software user interface is directly proportional to
Select one:
a. No of choices in the software interface
b. No of colors used in the software interface
c. None of the Answers
d. Indian standard Time
Ans: a. No of choices in the software interface
12. When designing user interface the idea is to keep in mind it should reflect implementation model.
Select one:
a. None of the answers
b. True
c. False
Ans: c. False
13. Perception driven by goals happens more in
Select one:
a. None of the Answers
b. Adults
c. Children
d. Both adults and kids
Ans: b. Adults
14. Identify the dominant gestalt principle.
Select one:
a. Closure
b. None of the Answers
c. Proximity
d. Similarity
Ans: c. Proximity
15. The prescriptive model that is helping you to calculate the time the user takes to make a decision in a user interface due to the many choices available is known as
Select one:
a. Fitt’s Law
b. Hick’s Law
c. None of the Answers
d. Newton’s distance Law
e. Movement Law
Ans: b. Hick’s Law
16. Sometimes our perceptions get filtered due to goals. An example of this:
Select one:
a. Muller-Lyer illusion
b. McGurk effect
c. Attentional Blink
d. Party Effect
Ans: d. Party Effect
17. User’s reaction time in a software User Interface is directly proportional to
Select one:
a. No of colors
b. No of disabled options
c. No of options/choices and the levels
d. Greenwich Mean Time
Ans: c. No of options/choices and the levels
18. What does the below image depict?
Select one:
a. Attentional Blink
b. Muller-Lyer illusion
c. McGurk effect
d. None of the Answers
Ans: b. Muller-Lyer illusion
19. Our perception can be influenced by
Select one:
a. Goals
b. None of the Answers
c. Both goals and future plans
d. Future plans
Ans: c. Both goals and future plans
20. Mental models could be achieved using
Select one:
a. None of the Answers
b. Perception-directed
c. Goal-directed
d. Self-directed
e. Concept based
Ans: c. Goal-directed
21. Which is not true related to wireframes.
Select one or more:
a. Used to communicate
b. Used for ideation
c. None of the Answers
d. Time Consuming
e. Expensive
Ans: d. Time Consuming
e. Expensive
22. Is it good to reduce the cognitive load on the users?
Select one:
a. None of the options
b. Yes
c. No
d. 50:50
Ans: b. Yes
23. Select Mechanical age representations
Select one or more:
a. Google calendar
b. Folder containing papers
c. Physical address book
d. None of the Answers
e. Paper calendar
Ans: b. Folder containing papers
c. Physical address book
e. Paper calendar
24. Stakeholder participate in providing information that are
Select one or more:
a. Technical challenges
b. User perceptions
c. None of the Anwers
d. Preliminary product vision
e. Budget
Ans: a. Technical challenges
b. User perceptions
d. Preliminary product vision
e. Budget
25. Successful products meet ____________ goals first
Select one:
a. Self
b. Non User
c. User
d. None of the Answers
e. Organizational
Ans: c. User
26. Perceptual Priming are based on
Select one:
a. Repetition
b. Realization
c. Response
d. Stimulus
Ans: d. Stimulus
27. Identify the principle that mind separates the visual field into
foreground and background?
Select one:
a. Closure
b. Symmetry
c. None of the Answers
d. Similarity
e. Continuity
Ans: c. None of the Answers
28. Muller-Lyer illusion is an example for
Select one:
a. Perception biased by Experience
b. Perception biased by Context
c. Perception biased by Movement
d. Perception biased by Goals
Ans: b. Perception biased by Context
29. What is the first step in information gathering?
Select one:
a. Visual design
b. Stakeholder interviews
c. None of the Answers
d. Prototyping
e. Wireframing
Ans: b. Stakeholder interviews
30. Fitt’s law helps to determine the
Select one:
a. Weight of an UI element
b. Color of an UI element
c. Distance of an UI element
d. Size of an UI element
e. Both size and distance of an UI element
Ans: e. Both size and distance of an UI element
31. Ventriloquism is an example of
Select one:
a. None of the Answers
b. Perception biased by experience
c. Perception biased by goals
d. Perception biased by context
Ans: d. Perception biased by context
32.Habituation happens because of
Select one:
a. Insight
b. Response
c. Stimulus
d. Reflex
Ans: d. Reflex
33. An experience that triggers an earlier memory and brings it at
the forefront of our mind and is called?
Select one:
a. Perceptual salience
b. The priming effect
c. Accessibility
d. None of the answers
Ans: b. The priming effect
34. McGurk effect demonstrates a bias between
Select one or more:
a. Hearing
b. Vision
c. Speech
d. Sense
Ans: a. Hearing
b. Vision
35. Identify the dominant gestalt principles
Select one:
a. Common Fate & Proximity
b. Similarity and Symmetry
c. Proximity & Continuity
d. Closure & Continuity
Ans: c. Proximity & Continuity
36. A model which exhibits the disconnection between an
implementation and what explains it is called
Select one:
a. Designer’s model
b. Mental model
c. Represented model
d. Implementation model
Ans: c. Represented model
37. Qualitative research helps to understand
Select one or more:
a. Behaviours
b. Attitudes
c. Domain of products
d. None of the Answers
e. Faults
Ans: a. Behaviours
b. Attitudes
c. Domain of products
38. Attentional blink is when you
Select one:
a. Lose focus
b. Lose confidence
c. Lose concentration
d. Lose memory
Ans: a. Lose focus
39. Usability testing helps in determining
Select one or more:
a. None of the Answers
b. Organization
c. Naming
d. How effective is the design
e. How easy to discover and use for the first time
Ans: d. How effective is the design
e. How easy to discover and use for the first time
40. The below image represents the gestalt principle of
Select one:
a. Proximity
b. None of the Answers
c. Symmetry
d. Common fate
e. Closure
Ans: e. Closure
Machine Learning Quiz 1 BITS PILANI WILP
Machine Learning (ISZC464) Quiz 1
BITS PILANI WILP - 2017
1. Averaging the output of multiple decision trees helps
Select one:
a. Increase bias
b. Increase variance
c. Decrease bias
d. Decrease variance
Ans: d. Decrease variance
2. Given genetic (DNA) data from a person, predict the odds of him/her developing diabetes over the next 10 years. What kind of learning problem is this?
Select one:
a. None of the given answers
b. Unsupervised Learning
c. Supervised Learning
d. Reinforcement Learning
Ans: c. Supervised Learning
3. Given a large dataset of medical records from patients suffering from heart disease, try to learn whether there might be different clusters of such patients for which we might tailor separate treatments. What kind of learning problem is this?
Select one:
a. Supervised Learning
b. Unsupervised Learning
c. None of the given answers
d. Reinforcement Learning
Ans: b. Unsupervised Learning
4. In farming, given data on crop yields over the last 50 years, learn to predict next year's crop yields. What kind of learning problem is this?
Select one:
a. None of the given answers
b. Unsupervised Learning
c. Reinforcement Learning
d. Supervised Learning
Ans: d. Supervised Learning
5. Suppose we wish to calculate P(H | E1, E2) and we have no conditional independence information. Which of the following sets are sufficient for computing this (minimal set)?
Select one:
a. P(E1, E2| H) , P(H), P(E1|H), P(E2|H)
b. P(H), P(E1| H), P(E2|H)
c. P(E1, E2) , P(H), P(E1|H), P(E2|H)
d. P(E1, E2), P(H), P(E1, E2| H)
Ans: c. P(E1, E2) , P(H), P(E1|H), P(E2|H)
6. Which of the following strategies cannot help reduce overfitting in decision trees?
Select one:
a. Enforce a maximum depth for the tree
b. Enforce a minimum number of samples in leaf nodes
c. Make sure each leaf node is one pure class
d. Pruning
Ans: c. Make sure each leaf node is one pure class
7. Suppose we wish to calculate P(H | E1, E2) and we know that P(E1| H, E2) = P(E1|H) for all the values of H, E1, E2. Now which of the following sets are sufficient?
Select one:
a. P(E1, E2| H) , P(H), P(E1|H), P(E2|H)
b. P(E1, E2) , P(H), P(E1|H), P(E2|H)
c. P(E1, E2), P(H), P(E1, E2| H)
d. P(H), P(E1| H), P(E2|H)
Ans: b. P(E1, E2) , P(H), P(E1|H), P(E2|H)
8. Take a collection of 1000 essays written on the US Economy, and find a way to automatically group these essays into a small number of groups of essays that are somehow "similar" or "related". What kind of learning problem is this?
Select one:
a. None of the given answers
b. Reinforcement Learning
c. Unsupervised Learning
d. Supervised Learning
Ans: c. Unsupervised Learning
9. Suppose you are working on weather prediction, and you would like to predict whether or not it will be raining at 5pm tomorrow. You want to use a learning algorithm for this. What machine learning task is this?
Select one:
a. Clustering
b. Classification
c. None of the given answers
d. Regression
Ans: b. Classification
10. You’ve just finished training a decision tree for spam classification, and it is getting abnormally bad performance on both your training and test sets. You know that your implementation has no bugs, so what could be causing the problem?
Select one:
a. You need to increase the learning rate.
b. Your decision trees are too shallow.
c. All of the other given options.
d. You are overfitting.
Ans: a. You need to increase the learning rate.
11. Which of the following statements about classification is true?
Select one:
a. As the number of data points grows to infinity, the MAP estimate approaches the MLE estimate for all possible priors. In other words, given enough data, the choice of prior is irrelevant
b. No classifier can do better than a naive Bayes classifier if the distribution of the data is known
c. Density estimation (using say, the kernel density estimator) can be used to perform classification
d. The depth of a learned decision tree can be larger than the number of training examples used to create the tree
Ans: c. Density estimation (using say, the kernel density estimator) can be used to perform classification
12. Consider the task of examining a large collection of emails that are known to be spam email, to discover if there are sub-types of spam mail. What kind of learning problem is this?
Select one:
a. Reinforcement Learning
b. Supervised Learning
c. Unsupervised Learning
d. None of the given answers
Ans: c. Unsupervised Learning
13. Suppose you are working on stock market prediction, and you would like to predict the price of a particular stock tomorrow (measured in dollars). You want to use a learning algorithm for this. What machine learning task is this?
Select one:
a. Classification
b. Clustering
c. Regression
d. None of the given answers
Ans: c. Regression
14. For polynomial regression, which one of these structural assumptions is the one that most affects the trade-off between underfitting and overfitting
Select one:
a. The assumed variance of the Gaussian noise
b. The use of a constant-term unit input
c. Whether we learn the weights by gradient descent
d. The polynomial degree
Ans: d. The polynomial degree
15. Which of the following statements is true?
Select one:
a. Given m data points, the training error converges to the true error as m →∞
b. Decision tree is learned by minimizing information gain
c. Linear regression estimator has the smallest variance among all unbiased estimators
d. A classifier trained on less training data is less likely to overfit
Previous page
Ans: a. Given m data points, the training error converges to the true error as m →∞
16. Given 50 articles written by male authors, and 50 articles written by female authors, learn to predict the gender of a new manuscript's author (when the identity of this author is unknown). What kind of learning problem is this?
Select one:
a. None of the given answers
b. Supervised Learning
c. Reinforcement Learning
d. Unsupervised Learning
Ans: b. Supervised Learning
Information Retrieval - Quiz 1 - BITS PILANI
Information Retrieval -SSZG537- Quiz 1 - BITS PILANI
Select one:
a. All of the above
b. Web-scale indexing
c. Google data centres
d. Parallel tasking
Ans: a. All of the above
2.Which is a good idea for using skip pointers?
Select one:
a. Fewer skips, larger skip spans
b. None
c. Depends upon the no. of comparisons needed
d. More skips, shorter skip spans
Ans: c. Depends upon the no. of comparisons needed
3. Edit distance (Levenshtein distance) is a way of:
Select one:
a. Context-sensitive spelling correction
b. Document correction
c. Isolated word correction
d. Phonetic correction
Ans: c. Isolated word correction
Select one:
a. Ranked search
b. Proximity search
c. Phrase search
d. Both proximity and ranked search
Ans: d. Both proximity and ranked search
Select one:
a. None
b. Boolean queries
c. Phrase queries
d. Wildcard queries
Ans: d. Wildcard queries
6. A large repository of documents in IR is called as:
Select one:
a. Corpus
b. Database
c. Dictionary
d. Collection
Ans: a. Corpus
7. Benefits of using a hash table is:
Select one:
a. Do not need to rehash everything periodically if vocabulary keeps growing.
b. Lookup in a hash table is faster than lookup in a tree.
c. All of the above
d. No prefix search is required
Ans: b. Lookup in a hash table is faster than lookup in a tree.
8. Variable-size postings lists is used when:
Select one:
a. More seek time is desired and the corpus is dynamic
b. Less seek time is desired and the corpus is dynamic
c. Less seek time is desired and the corpus is static
d. More seek time is desired and the corpus is dynamic
Ans: d. More seek time is desired and the corpus is dynamic
9. An alternative to equivalence classing is to do:
Select one:
a.Asymmetric expansion
b. Symmetric expansion
c. Case folding
d. Normalization
Ans: d. Normalization
10. We need external sorting algorithms to:
Select one:
a. Maximize the disk seek time.
b. Maintain constant disk seek time
c. Minimize the disk seek time.
d. None
Ans: c. Minimize the disk seek time.
11. Benefits of using B-trees:
Select one:
a. Re-balancing is cheap
b. Balanced trees allow efficient retrieval
c. Faster O(log M)
d. Solves the prefix problem.
Ans: d. Solves the prefix problem.
Select one:
a. Document Frequency
b. DocID
c. TermID
d. Term frequency
Ans: b. DocID
13. Key idea behind Single-pass in-memory indexing is:
Select one:
a. Don’t sort, Accumulate postings in postings lists as they occur.
b. Generate separate dictionaries for each block.
c. All of the above
d. No need to maintain term-termID mapping across blocks.
Ans: c. All of the above
14. For postings of length L, no. of skip pointers required are:
Select one:
a. Use L evenly-spaced skip pointers
b. Use L^2 evenly-spaced skip pointers.
c. Use L^1/2 evenly-spaced skip pointers
d. Use 2L evenly-spaced skip pointers.
Ans: c. Use L^1/2 evenly-spaced skip pointers
15. For query optimization while intersecting two postings list, we should:
Select one:
a. Process in the order of increasing document frequency
b. Process in any order
c. None of the above
d. Process in the order of decreasing document frequency
Ans: a. Process in the order of increasing document frequency
16. The goal of IR is to:
Select one:
a.find documents relevant to an information need
b. find documents relevant to an information need from a given document set
c. find documents relevant to an information need from a large document set
d. find documents relevant to an information need from a small document set
Ans: c. find documents relevant to an information need from a large document set
17. Best implementation approach for dynamic indexing is:
Select one:
a. Periodic re-indexing
b. Using Invalidation bit-vector for deleted docs
c. None
d. Using logarithmic merge
Ans: d. Using logarithmic merge
Select one:
a. Any one
b. Index blowup due to bigger dictionary
c. Both
d. False positives
Ans: c. Both
19. Any string of terms of the following form is called an extended biword:
Select one:
a. NNX*
b. NXNN
c. *NNX
d. NX*N
Ans:d. NX*N
20. Structured data allows for:
Select one:
a. Does not depend on data complexity
b. Less complex queries
c. No relationship
d. More complex queries
Ans: d. More complex queries
21. Blocked sort-based Indexing is a method of:
Select one:
a. Sorting with more disk seeks.
b. Merging with fewer disk seeks.
c. Comparing with fewer disk seeks.
d. Sorting with fewer disk seeks.
Ans: a. Sorting with more disk seeks.
22. Term-document incidence matrix is:
Select one:
a. Sparse
b. Depends upon the data
c. Dense
d. Cannot predict
Ans: a. Sparse
23. Lemmatization is a technique for:
Select one:
a. Ranking documents
b. Case folding
c. Normalization
d. Tokenization
Ans: c. Normalization
24. If list lengths are x and y, merge takes:
Select one:
a. O(Yn) operations
b. O(xy) operations
c. O(xn) operations
d. O(x+y) operations
Ans: d. O(x+y) operations
25. Unstructured data tends to refer to information on the web and is processed using:
Select one:
a. Both
b. Database systems
c. IR systems
d. None
Ans: c. IR systems
Data Mining Quiz1 ISZC415 - BITS PILANI WILP MTEC
Data Mining Quiz 1 ISZC415 - BITS PILANI WILP MTEC
1. 27, 0, 1, 2, 63, 61, 0, 13
The five number summary of the above sample is:
Select one:
a. 63, 27, 13, 2, 0
b. 0, 2, 13, 27, 63
c. 0, 1, 13, 27, 63
d. 0, 0.5, 7.5, 44, 63
Ans: d. 0, 0.5, 7.5, 44, 63
Select one:
a. weighted mean
b. midrange
c. median
d. mean
Ans: c. median
3. Validation set and test set contain the same samples.
Select one:
True
False
Ans: False
4. A boxplot can show outliers as small circles/points,
Select one:
True
False
Ans: True
5. Analysis of patterns for stock market prediction is an example of:
Select one:
a. evolution analysis
b. outlier analysis
c. correlation
d. characterization and discrimination
Ans: a. evolution analysis
6. Pearson's product moment correlation coefficient between two
variables can have values:
Select one:
a. 0 or any positive number
b. greater than or equal to -1 but less than or equal to +1
c. greater than 0 but less than one
d. 0 or positive but less than or equal to 1
Ans: b. greater than or equal to -1 but less than or equal to +1
7. Given two text documents, when we shuffle the words of any one of
the documents, the cosine similarity between the two texts will not
change.
Select one:
True
False
Ans: True
8. If all the tuples in a data set belong to a single class, then its
gini index is:
Select one:
a. 0.5
b. insufficient information to say anything
c. 0
d. 1
Ans: c. 0
9. The mapping of a value by min-max normalization is always in the
range [0,1]
Select one:
True
False
Ans: False
10. We always predict some amount or number in this kind of problems:
Select one:
a. classification
b. preprocessing
c. clustering
d. regression
Ans: d. regression
11. Holistic measure can be derived from distributive measures
Select one:
True
False
Ans: False
12. If all the data values in a set of data are unique, then
Select one:
a. their is no mode
b. we can select any one number as mode
c. the median is the mode
d. all the numbers are modes
Ans: a. their is no mode
13. A boxplot is nothing but a visual representation of IQR
Select one:
True
False
Ans: False
14.10, 2, 3, 4, 5, 3, 4, 6, 2
How many modes are there?
Select one:
a. 2
b. 1
c. 3
d. 4
Ans: c. 3
15. 10, 2, 3, 4, 5
The midrange of the above sample set is:
Select one:
a. 3
b. 6
c. 7.5
d. 4
Ans: b. 6
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