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Logical Reasoning

2/7/2011

1 Comment

 
Blood Relationships

A is the father of C. But C is not his son. E is the daughter of C. F is the spouse of A. B is the brother of C. D is the son of B. G is the spouse of B. H is the father of G.

21. Who is the grandmother of D?

(a) A      (b) C           (c) F        (d) H

22. Who is the son of F?

(a)B       (b) C        (c) D        (d) E

23. Sheela said that, “Sachin is the only brother of the husband of the mother of my husband” How is Sachin’s only brother related to Sheela?

(a) Grandson      (b) Son     (c) Father-in-law   (d) Husband          (e) None of these

Directions :(i) 'A $ B' means 'A is mother of B'

                (ii) 'A # B' means 'A is father of B'

                (iii) 'A @ B' means 'A is husband of B'

                (iv) 'A % B' means A is daughter of B'

24. Which of the following expressions indicates 'R is the sister of H'?

(a) H $ D @ F $ R                         

(b) R % D @ F $ H                       

(c) R # D @ F $ H

(d) H% D @ F $ R

25. If F @ D% K # H, then how is F related to H?

(a) Brother-in-law                        

(b) Sister                                     

(c) Sister-in-law

(d) Cannot be determined

26. Which of the following expressions indicates 'H is the grandfather of N'?

(a) H $ R $ D $ N                         

(b) H # F @ D $ N

(c) N % F @ D $ H

(d) N % F@ D % H

Mathematical Operations

A $ B means A is smaller than B.

A * B means A is neither smaller than nor greater than B.

A # B means A is either greater than or equal to B.

A % B means A is greater than B.

A © B means A is either smaller than or equal to B.

Now in each of the following questions, assuming the three statements to be true, state which of the two conclusions I and II given below them is definitely true.

Give answer

(A) if only conclusion I is true;

(B) if only conclusion II is true;

(C) if either I or II is true;

(D) if neither I nor II is true and

(E) if both I and II are true.

  27. Statements: B # D, D * F, F % H

Conclusions: I. F * B          II. F $ B

28.  Statements : H $ J, J * N, N # T

Conclusions: I. T % H           II. J # T

29.  Statements: M % K, K # T, T * J

Conclusions: I. J © K          II. T $ M

30. Statements: W © F, F % R, R # K

Conclusions: I. W $ K         II. K * W

31. Statements: V © R, R $ M, M * W

      Conclusions: I. W % V        II. V © W

Coding-Decoding

32. If GROUND is coded as LXTASJ in a certain code, how would CONGRATULATIONS be written in that code?

(a) HUSMVGYAQGYOSTY (b)HUSMWGYAQGYOTTX      (c) HUTMWGYAQGYPTTX   (d) HUSMWHYAQGYOTTX              

(e) HUSNWGYAQGYOTUX

Directions: In a certain code

 "7861" means "bring me apple red"

 "9538" means "peel green apple once"  

 "6475" means "bring me green fruit"

 “3624” means “once bring fruit yellow”

33. Which of the following is the code for "bring”?

(a) 8      (b) 6      (c) 7 (d) 5

34. Which is the code for “red”?

 (a) 1      (b) 6      (c) 7         (d) 8

35. Digit ‘4’ represents which word?

(a) peel  (b) green   (c) apple   (d) fruit

Series

36. How many terms are there in the series 114, 117, 120, 123, …, 300

a)65     b) 67    c) 62    d) 63

37. 41, 43, 47, 53, 59, ….

a)61     b) 63    c) 65    d) 67

38. 2, 10, 30, 68, 130, ….

a)210   b) 212  c) 225  d) 222

Tracing Sequential Output

Study the following input of a message and four steps that come after it brought out by a rearrengement machine.

Input: JBIMS is the best institute

Step I: is JBIMS the best institute

Step II: is the JBIMS best institute

Step III: is the best JBIMS institute

Step III is the last step of this output.

Following the rules of the above tracing of the sequential output, answer the following questions.

39. Which of the following is the V step for the given input?
  Input: Information available could be read but perfection denied

a) be but read denied Information available could perfection

b) be but read denied could Information available perfection

c) be but read could denied Information available perfection

d) be but read could denied available Information perfection

 

40. Step 2: a is cracking entrances not tough task.

Which step will be the final step?

a) 4th    b) 5th   c) 6th   d) 7th

 

41. If step III is: a was once cricketer Yuvraj Singh.

Which of the following can be the input?

a) Yuvraj Singh was a once cricketer

b) a Singh cricketer Yuvraj was once

c) cricketer Yuvraj Singh was a once

d) Yuvraj Singh was a cricketer once

 

Syllogisms

Direction: In each of the following questions two statements are given, followed by two conclusions numbered I and II. You have to take the two given statements to be true even if they seem to be at variance with the commonly known facts and then decide which of the given conclusions logically follows from the two given statements, disregarding commonly known facts.

Give answer :   (a) if only conclusion I follows.

(b) if only conclusion II follows.

(c) if either I or II follows.

(d) if neither I nor II follows.

(e) if both I and II follow.

 

42. Statements

P: Some kings are queens.

Q: All queens are beautiful.

Conclusions

I. Some kings are beautiful.

            II. All queens are kings.

 

43. Statements

P : All balls are bats.

Q: All bats are stumps.

Conclusions

I. All balls are stumps.

II. All stumps are balls.

 

44. Statements

P: All rats are boats.

Q: No boat is a cat.

Conclusions

I. All cats are rats.

II. No rat is a cat.

 

45. Statements

P: All good athletes want to win.

Q: All good athletes eat well.

Conclusions

            I. All those who eat well are good athletes.

            II. All those who want to win, eat well.

 

46. Statements

P: All buds are flowers.

Q: Some flowers are thorns.

Conclusions

I. Some buds are thorns.

II. No bud is thorn.

 

47. Statements

P : Some mobiles are cameras.

Q: some cameras are calculators.

Conclusions

I. Some mobiles are calculators.

II. No mobiles are calculators.

 

Directions: Each of thefollowing questions consist of some statement followed by some conclusions. Consider the statement to be true even if they very from the commonly known facts and find out which of the conclusions logically follow the given statement and close the proper alternative from the given choices.

 

48. Statements:

      All planets are stars.

      All moons are planets.

      Some stars  do not shine.

      Conclusions:

I.             All moons are star.

II.            Some planets do not shine.

III.          No star shines.

IV.           All planets shine

a) Either II or IV follows

b) Only I and II follows

c) Only I and Either II or IV follow

d) Only I and III follow

e) None of these.

 

49. Statements:

      All coconuts are groundnuts.

      Some groundnuts are peanuts.

      Some peanuts are cashew nuts.

      Conclusions:

I.             Some coconuts are cashew nuts.
II.             Some peanuts are coconuts.
III.            All groundnuts are coconuts.
IV.          No coconut is a cashew nut.

a) Only I and II follow

b) Only II and IV follow

c) Only III follows

d) Either I or IV follows

e) None follows

 

50. Statements:

      All happy are peaceful.

      Some tensed are happy.

      No happy is upset.

      Conclusions:

I.             Some tensed are peaceful.

II.            All upset are peaceful.

III.          All happy are tensed.

IV.           Some happy are tensed.

a) Only I follows

b) Only I and IV follow

c) Only III follows

d) Only I and either III or IV follow

e) None of these

 

51. Statements:

Some eyes are teeth.

All teeth are ears.

All eyes are lips.

      Conclusions:

I.             Some lips are teeth.

II.            Some ears are eyes.

III.          Some ears are lips.

IV.           Some lips are eyes.

a) Only I and II follow

b) Only I,II and III follow

c) Only I,III and IV follow

d) Only II,III and IV follow

e) All follow.

 

52. Statements:

Some mornings are evenings.

Some nights are afternoons.

All nights are mornings.

      Conclusions:

I.             Some afternoons are mornings.

II.            Some nights are evenings.

III.          All mornings are nights.

IV.           All afternoons are evenings.

a) Only I follows

b) Only I and II follow

c) Only III follows

d) Only IV follows

 

 

Miscellaneous

53. How many pairs of letters exist in the word VIRULENT such that the relative distance between them in the word is the same as the relative distance between them in the English alphabet?

a) One       b) three      c) four       d) five        e) two

 

Alpha numeric sequence puzzle

Directions: Study the following arrangement carefully and answer the questions given below:

TI5Q79B#2K%U1MWA4*J8

54. How many such vowels are there in the above arrangement, each of which is immediately followed by a number but not immediately preceded by a consonant?

(a) None        (b) One            (c) Two            

(d) Three       (e) None of these

 

55. Which of the following is seventh to the left of the sixteenth from the left in the above arrangement?

(a) A              (b) U                (c) 2    

(d) #            (e) None of these


Critical reasoning

 


Directions: Answer the questions based on the following information.

 

Each of the five persons A, B, C, D, E plays a different game like football, tennis, cricket, badminton and volley ball. Each one has been selected to be part of the All India Games Association in different year among 2006, 2007, 2008, 2009 and 2010. Further it is known that

·         The person playing tennis was selected for year 2007, but he is neither B nor C.

·         D and E were selected for the year 2008 and 2010, respectively.

·         Neither D nor C plays cricket.

·         B plays football and got selected before C.

 

56. Which game does C play?

a) Football    b) volleyball c) badminton d) Either b or c

e) Either a or c

 

57. Who plays cricket and in which year?

a) A, 2007              b) B, 2010          c) E, 2010            d) D, 2008       e) Cannot be determined     

 

58. Which of the following is definitely correct combination of person, sport and year?


a) A, tennis, 2007         b) C, badminton, 2009

c) E, tennis, 2008               d) B, volleyball, 2005

e) None of these   

 

59. Who was selected for the year 2009?

a) C            b) D             c) A           d) Either A or C

e) Either A or B

     

60. If C plays volleyball, which game does D play?

a) Football        b) badminton      c) Lawn tennis

d) Volleyball         e) cannot be determined










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  • Applied Analytics
    • Analytics for Decision Making >
      • What is Cluster Analysis
      • Data Reduction and Unsupervised Learning
      • Preparing Data and Measuring Dissimilarities
      • Hierarchical and k-Means Clustering
      • Defining Output Variables and Analyzing the Results
      • Using Historical Data to Model Uncertainty
      • Models with Correlated Uncertain Variables
      • Creating and Interpreting Charts
      • Using Average Values versus Simulation
      • Optimization and Decision Making
      • Formulating an Optimization Problem
      • Developing a Spreadsheet Model
      • Adding Optimization to a Spreadsheet Model
      • What-if Analysis and the Sensitivity Report
      • Evaluating Scenarios and Visualizing Results to Gain Practical Insights
      • Digital Marketing Application of Optimization
      • Advanced Models for Better Decisions
      • Business Problems with Yes/No Decisions
      • Formulation and Solution of Binary Optimization Problems
      • Metaheuristic Optimization
      • Chance Constraints and Value At Risk
      • Simulation Optimization
    • Analytics for Marketing >
      • Marketing Analytics and Customer Satisfaction
      • Customer Satisfaction
      • Measurements and Scaling Techniques – Introduction
      • Primary Scales of Measurement
      • Comparative Scaling
      • Non-Comparative Scaling
      • Experiment Design: Controlling for Experimental Errors
      • A/B Testing: Introduction
      • A/B Testing: Types of Tests
      • ANOVA – Introduction
      • Example -Inspect Spray and Tooth Growth
      • Logit Model - Binary Outome and Forecastign linear regression
      • Text Summarization
      • Social media Microscope
      • N-Gram - Frequcy Count and phase mining
      • LDA Topic Modeling
      • Machine-Learned Classification and Semantic Topic Tagging
    • Data Engine >
      • Understanding The Growth Of Data
      • Evaluating Methods Of Data Access
      • Communication journey
      • Data Journey
      • Planning for data visualisation
      • Visualisation Component
      • Content Connection and Chart Legitibility
    • Customer Insights >
      • Introduction
      • What is Descriptive Analytics?
      • Survey Overview
      • Net Promoter Score and Self-Reports
      • Survey Design
      • Passive Data Collection
      • Media Planning
      • Data Visualization
      • Causal Data Collection and Summary
      • Asking Predictive Questions
      • Regression Analysis
      • Data Set Predictions
      • Probability Models
      • Results and Predictions
      • Perspective Analytics (Maximize Revenue and Market Structure Competitions)
    • Analytics for Advance Marketing >
      • Visualisation and statistics (Political Advertising,Movie Theater and Data Assembly)
      • Excel Analysis of Motion Picture Industry Data
      • Displaying Conditional Distributions
      • Analyzing Qualitative Variables
      • Steps in Constructing Histograms
      • Common Descriptive Statistics for Quantitative Data
      • Regression-Based Modeling
      • Customer Analytics
      • Illustrating Customer Analytics in Excel
      • Customer Valuation Excel Demonstration
  • Soft Skills
    • Adaptability
    • Confidence
    • Change Management
    • Unlearning and Learning
    • Collaboration and Teamwork
    • Cultural Sensitivity
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  • Finance
  • Economics
    • Introduction to Managerial Economics >
      • Basic Techniques
      • The firm: Stakeholders, Objectives and Decision Issues
      • Demand and Revenue Analysis >
        • Demand Estimation and Forecasting
        • Demand Elasticity
        • Demand Concepts and Analysis >
          • Formulation and Solution of Binary Optimization Problems
      • Scope of Managerial Economics
    • Prodution and Cost Analysis >
      • Production Function
      • Estimation of Production and Cost Functions
      • Cost Concepts and Analysis I
      • Cost Concepts and Analysis II
    • Pricing Decisions >
      • Pricing strategies >
        • Adding Optimization to a Spreadsheet Model
      • Market structure and microbes barriers to entry
      • Pricing under pure competition and pure monopoly
      • Pricing under monopolistic and oligopolistic competition
    • Narendra Modi Development Model of Gujarat
  • JBDON Golf
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  • Let's Talk
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  • About Us
    • Good Read >
      • IIMC says PepsiCo CEO Indra Nooyi was an average student
      • India’s middle class figures in Fortune’s Top Ten list of those who matter
      • The Start-Up of you.
      • BUYING AND MERCHANDISING
      • HUMAN RESOURCE MANAGEMENT
      • Do You Suffer From Decision Fatigue?
      • New Page
      • About social media and web 2.0
      • Building Your Own Start-up Technology Company, Part 1
      • Building Your Own Start-up Technology Company, Part 2
      • Building Your Own Start-up Technology Company, Part 3
      • Building Your Own Start-up Technology Company, Part 4
      • Renewable energy is no longer alternative energy
      • What Makes an Exceptional Social Media Manager?
      • The Forgotten Book that Helped Shape the Modern Economy
      • Home
      • How to Think Creatively
      • A Lighthearted Looks at Project Management and Sports Analogies
      • Why Trust Matters More Than Ever for Brands
  • CET Knowledge Zone
    • Tips From JBIMS Students >
      • Prasad Sawant
      • Chandan Roy
      • Ram
      • Ashmant Tiwari
      • Rajesh Rikame
      • Ami Kothari
      • Ankeet Adani
      • Sonam Jain
      • Marketing Analytics and Customer Satisfaction
      • Mitesh Thakker
      • Tresa Sankoorikal
    • Speed Techniques
    • CET Workshops
  • Untitled
  • New Page
    • Cluster analysis using excel and excel miner
    • Chance Constraints and Value At Risk
    • Adding Uncertainty to a Spreadsheet Model
  • Adidas