17 Jun 2017

Important Tips to approach Missing Data Interpretation for IBPS Exams 2017

Important Tips to approach Missing Data Interpretation for IBPS Exams 2017
Important Tips to approach Missing Data Interpretation for IBPS Exams 2017:
Dear Readers, Nowadays often we can expect Missing Data Interpretation questions in examinations, many of our site followers were requesting to provide tips to approach these type questions, to fulfill your request here we have given the Important Tips to approach Missing Data Interpretation for IBPS Exams 2017. Candidates those who are preparing for the examination can make use of it.





Introduction:
·        Missing Data Interpretation questions have become a part of all competitive examinations nowadays. This is especially true in SBI - PO and IBPS - PO exam. These questions are like any other DI questions but might seem difficult in the first attempt.
·        We know that, Missing DI will consist of tabular charts/tables where certain fields are blank. Candidates are required to find the value of these missing blanks and use these values to solve the questions.
Guidelines to solve Missing DI:
·        The questions are easy to solve provided that the candidates are aware of the proper way to attempt them.
·        Keeping this view in mind, we have provided some instructions which will assist candidates about the proper method to use while solving missing data interpretation questions so that they can save their time while answering.
·        In missing DI, some data are missing. But the trick is that it only looks like data is missing. In reality, all the data are already there; they are just hidden.
·        In the Missing DI question you can follow two methods:
o   Fill all blank space given in the table       
o   According to question try to solve due to more blank space in the table.

Solved Examples:
Example 1: (Easy)
Directions: The proportion of female employees and the proportion of Ph. D scholars in a company are given below. The company has a total of 700 employees, 60% of whom are in the HR department and the rest equally divided between the Development and the Testing department.
Department
Female
Ph. D scholars
Development
0.50

Testing
0.45
0.60
HR

0.45
Total
0.51
0.73

1). What is the percentage of female employees in the HR department (approx)?
a)   41%
b)   47%
c)   53%
d)   55%
e)   68%
Answer: e)
Explanation:
In this question, total no. of employees and the % of employees in HR department are given. In table, the ratio of the (i.e. x/100) female and Ph. D scholars were given. On the basis of given values we can easily find out the values of blanks in the table.
Total number of female employees in the company= 0.51 of 700= 357
We now have to see how many of these are from HR department.
Number of employees in HR department = 60% of 700= 420
Number of employees in Development = 20% of 700
Number of Female employees in Development = 0.50 of 20% of 700 = 70
Number of Female employees in Testing = 0.45 of 20% of 700 = 63
Female employees in HR department = 357 - (70 + 63) = 224
Percentage of Female employees in HR = (224/420) x 100= 53.33%
Similarly, we can find the no. of Ph.D scholars in each department of the company. 
Note: For this type of missing DI we should calculate the missing values of table first. Then solving the questions will be easy.

Example 2: (Moderate - Difficult)
Directions: A group of 5 players Arjun, Bindhu, Charan, Dinesh and Elan participated in a ‘cricket’ tournament and played four days (1 to 4). The following table gives partial information about their individual scores and the total runs scored by the team in each day.
Players
Day 1
Day 2
Day 3
Day 4
Arjun

120

63
Bindhu
88
65

61
Charan


130

Dinesh
92
82
25
76
Elan
80

68

Total
320
330
260
240

In this DI, two values are missing in each column. These are the runs scored by the two lowest scorers in that day. None of the two missing values is more than 10% of the total runs scored in that day.
1) What is the maximum possible percentage contribution of Arjun in the total runs scored in 4 days?
a)   20.78%
b)   19.98%
c)   20.18%
d)   20.28%
e)   None of these
Answer: Option A
Explanation:
Now we have no clue about Arjun’s score in day 1 and 3.
So we must consider the statement: “None of the two missing values is more than 10% of the total runs scored in that day.
Maximum possible runs scored by Arjun in Day 1 = 10% of 320 = 32
Maximum possible runs scored by Arjun in Day 3
= 24 (Since the 3rd lowest score of the day is 25. So Arjun’s score should be less than 25).
So, Maximum possible percentage contribution:
(32+120+24+63) / (320+330+260+240) x 100% = 239 / 1150 x 100% = 20.78%
Note: For this type of question in missing DI we need not calculate the missing values of table first, since there are more no. of blanks. So we can find the values according to the information given in the question.

2). If the absolute difference between the total runs scored by Arjun and Charan in the four days is minimum possible then what is the absolute difference between total runs scored by Bindhu and Elan in the four days?
a)   32
b)   44
c)   27
d)   Cannot be determined
e)   None of these
Answer: b)
Explanation:
Maximum possible total runs scored by Charan in the four days
= 32 + 33 + 130 + 24 = 219.
(By taking 10% values of total score in each day).

Completing the table:
Players
Day 1
Day 2
Day 3
Day 4
Arjun
28
120
13
63
Bindhu
88
65
24
61
Charan
32
33
130
24
Dinesh
92
82
25
76
Elan
80
30
68
16
Total
320
330
260
240

Note: In Day 3, we have considered Bindhu’s score as 10% of total score on that day. So only, the difference between total score of Arjun and Charan will be Minimum. So we have taken minimum possible score of Arjun.
In such a case minimum possible total runs scored by Arjun in the four days
= 28 + 120 + 13 + 63 = 224.
Difference = 224 – 219 = 5 (minimum possible)
Subsequently total runs scored by Bindhu in the four days
= 88 + 65 + 24 + 61 = 238.
Also, total runs scored by Elan in the four days = 80 + 30 + 68 + 16 = 194
Absolute difference = 238 – 194 = 44.

Note: For this type of question in missing DI we have to calculate the missing values of table first, otherwise we cannot answer the question. After finding the missing values, we can solve the question.

        


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