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Quantitative Aptitude - Data Interpretation Questions

What is Quantitative Aptitude- Data Interpretation?

 

Data Interpretation is the process of analysing data, inspecting the elements in data and Interpreting to extract maximum information from the given set of data or information. The data is given in the form of charts, tables and graphs. Data Interpretation has no particular syllabus, this section tests one's ability in analysing data, decision making capability and speed. Data Interpretation looks simple and easy but the calculations are time consuming. For solving the data interpretation problems efficiently one should analyse the given data and focus on aspects of the data that are necessary to answer the questions, before attending data interpretation section one should be very comfortable with numbers, calculations, percentages, fractions, averages and ratios to increase the calculation speed.

 

We come across Data Interpretation Questions in many competitive exams and Entrance Tests like Bank Exams (SBI PO), MBA entrance exams (CAT, MAT), HPAS, APPSC group1, HR executives, UPSC CPF (AC),IBPS ,UP Police constable exams, TNPSC VAO, WBSC, PPSC, HAL Results, NDA, Lokhsabha secretariat, Rajyasabha secretariat exams and more

 

Thorough practice of different papers on data interpretation allows you to solve different kinds of data interpretation and can help improve your logic in solving problems.

 

We have a large database of questions on Quantitative Aptitude (Data Interpretation) for you to practice and score high.

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Q:

Study the following line graph and answer the questions based on it.

Number of Vehicles Manufactured by Two companies ove the Years (Number in Thousands)

 

1. What is the difference between the number of vehicles manufactured by Company Y in 2000 and 2001 ?

A. 50000                   B. 42000                   C. 33000                   D. 21000

 

2. What is the difference between the total productions of the two Companies in the given years ?

A. 19000                   B. 22000                   C. 26000                   D. 28000

 

3. What is the average numbers of vehicles manufactured by Company X over the given period ? (rounded off to nearest integer)

A. 119333                 B. 113666                 C. 112778                 D. 111223

 

4. In which of the following years, the difference between the productions of Companies X and Y was the maximum among the given years ?

A. 1997                     B. 1998                     C. 1999                     D. 2000

 

5. The production of Company Y in 2000 was approximately what percent of the production of Company X in the same year ?

A. 173                       B. 164                       C. 132                       D. 97

Answer

1. ANSWERS  : D  


Explanation-   Required difference = (128000 - 107000) = 21000.


 


2. ANSWERS  : C  


Explanation-  From the line-graph it is clear that the productions of Company X in the   years 1997, 1998, 1999, 2000, 2001 and 2002 are 119000, 99000, 141000, 78000, 120000 and 159000 and those of Company Y are 139000, 120000,100000, 128000, 107000 and 148000 respectively. 


Total production of Company X from 1997 to 2002 


= 119000 + 99000 + 141000 + 78000 + 120000 + 159000 


= 716000. 


and total production of Company Y from 1997 to 2002 


= 139000 + 120000 + 100000 + 128000 + 107000 + 148000 


= 742000. 


Difference = (742000 - 716000) = 26000.


 


3. ANSWERS  : A 


Explanation-  Average number of vehicles manufactured by Company X  


= 16×119000+99000+141000+78000+120000+159000 


 = 119333.


 


4. ANSWERS  : D  


Explanation-   The difference between the productions of Companies X and Y in various years are: 


 For 1997 (139000 - 119000)  = 20000. 


 For 1998 (120000 - 99000)  = 21000. 


 For 1999 (141000 - 100000)  = 41000. 


 For 2000 (128000 - 78000) = 50000. 


 For 2001 (120000 - 107000) = 13000. 


 For 2002 (159000 - 148000) = 11000. 


 Clearly, maximum difference was in 2000.


 


5. ANSWERS  :  B


Explanation  - Required percentage= 12800078000×100 % = 164%

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Subject: Line Charts - Quantitative Aptitude - Data Interpretation

22 7851
Q:

The following pie chart shows the amount of subscriptions generated for India Bonds from different categories of investors.

1. In the corporate sector, approximately how many degrees should be there in the central angle ?

A. 120                 B. 121                 C. 122                 D. 123


2. If the investment by NRI's are Rs 4,000 crore, then the investments by corporate houses and FII's tog ether is:

A. 24,000 cr       B. 24,363 cr       C. 25,423 cr       D. 25,643 cr


3. What percentage of the total investment is coming from FII's and NRI's ?

A. 33%                B. 11%                C. 44%                D. 22%


4. If the total investment other than by FII and corporate houses is Rs 335,000 crore, then the investment by NRI's and Offshore funds will be (approximately) ?

A. 274,100         B. 285,600         C. 293,000         D. Cannot be determined


5. If the total investment flows from FII's were to be doubled in the next year and the investment flows from all other sources had remained constant at their existing levels for this year, then what would be the proportion of FII investment in the total investment into India Bonds next year (in US $ millions) ?

A. 40%                B. 50%                C. 60%                D. 70%

Answer

1. ANSWER :   C 


Explanation -   34 x 3.6 = 122.4 (since 1% = 3.6 degrees)  


  


2. ANSWER :  B 


Explanation -   (67/11) x 4000 = 24 363.6364   


 


3. ANSWER :  C


Explanation -  (33 + 11) = 44 


 


4. ANSWER :  A


Explanation -  Investment other than NRI and corporate houses is 33% = 335000.  Also, investment by offshore funds and NRI's is equal to 27%.


 Hence, (27 x 335000)/33 = 274 090.909


 


5. ANSWER : B


Explanation -  FII's currently account for 33 out of 100.


If their value is doubled and all other investments are kept constant then their new value would be 66 out of 133 = approximately equal to 50%

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Subject: Pie Charts - Quantitative Aptitude - Data Interpretation

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