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CPT Section D Quantitative Aptitude, Chapter14 
Prof. (Dr.) P . R. Vittal 
Page 2


CPT Section D Quantitative Aptitude, Chapter14 
Prof. (Dr.) P . R. Vittal 
Binomial Distribution 
Page 3


CPT Section D Quantitative Aptitude, Chapter14 
Prof. (Dr.) P . R. Vittal 
Binomial Distribution 
(a)1/2  
(b)1/4    
(c)3/8  
(d)(1/8)  
Answer:(c) 
8 / 3 ) 4 / 1 ( ) 4 / 1 ( 6 ) 2 / 1 ( ) 2 / 1 ( 4
2 2
2
= = X X C
x n x
x
q p nC x P
-
= ) (
on Distributi Binomial a In 
Page 4


CPT Section D Quantitative Aptitude, Chapter14 
Prof. (Dr.) P . R. Vittal 
Binomial Distribution 
(a)1/2  
(b)1/4    
(c)3/8  
(d)(1/8)  
Answer:(c) 
8 / 3 ) 4 / 1 ( ) 4 / 1 ( 6 ) 2 / 1 ( ) 2 / 1 ( 4
2 2
2
= = X X C
x n x
x
q p nC x P
-
= ) (
on Distributi Binomial a In 
64 / 15
) 2 / 1 ( ) 2 / 1 ( 6 ) 2 (
4 2
2
=
= = C x P
(a)15/64   
(b)3/64   
(c)3/32  
(d)5/32 
Answer:a 
Page 5


CPT Section D Quantitative Aptitude, Chapter14 
Prof. (Dr.) P . R. Vittal 
Binomial Distribution 
(a)1/2  
(b)1/4    
(c)3/8  
(d)(1/8)  
Answer:(c) 
8 / 3 ) 4 / 1 ( ) 4 / 1 ( 6 ) 2 / 1 ( ) 2 / 1 ( 4
2 2
2
= = X X C
x n x
x
q p nC x P
-
= ) (
on Distributi Binomial a In 
64 / 15
) 2 / 1 ( ) 2 / 1 ( 6 ) 2 (
4 2
2
=
= = C x P
(a)15/64   
(b)3/64   
(c)3/32  
(d)5/32 
Answer:a 
(a)7,8   
(b)6,7 
(c)6,3 
(d)5,7  
Answer:a 
Solution : 
In a binomial distribution  
(n+1)p = 24/3 = 8. It has 2 
modes 7 and 8. 
 Ans : (a) 
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FAQs on MCQ - Theoretical Distribution - Quantitative Aptitude for CA Foundation

1. What is a theoretical distribution in the context of CA Foundation?
Ans. A theoretical distribution, in the context of CA Foundation, refers to a mathematical function that describes the likelihood of different outcomes occurring in a specific scenario. It helps in understanding the probability of various events or values in a given situation, such as the distribution of marks in an exam or the distribution of profits in a business.
2. How is a theoretical distribution used in CA Foundation exams?
Ans. Theoretical distributions are used in CA Foundation exams to analyze and interpret data, make predictions, and make informed decisions. By understanding the theoretical distribution of data, candidates can calculate probabilities, assess risks, and evaluate the likelihood of different outcomes. This knowledge is crucial for effective financial analysis and decision making.
3. What are some commonly used theoretical distributions in CA Foundation exams?
Ans. Some commonly used theoretical distributions in CA Foundation exams include the normal distribution, binomial distribution, and Poisson distribution. The normal distribution is often used to model continuous data, while the binomial distribution is used for binary or categorical data. The Poisson distribution is commonly applied to situations where the occurrence of events is rare but can be counted.
4. How can candidates apply theoretical distributions in financial analysis?
Ans. Candidates can apply theoretical distributions in financial analysis by using statistical techniques to analyze and interpret data. For example, they can calculate the probability of a certain return on investment based on the historical distribution of returns. This information can then be used to assess the risk associated with an investment, make informed decisions, and develop effective financial strategies.
5. Are there any limitations or assumptions associated with theoretical distributions in CA Foundation exams?
Ans. Yes, there are some limitations and assumptions associated with theoretical distributions in CA Foundation exams. One major assumption is that the data being analyzed follows a specific distribution, which may not always be the case in real-world scenarios. Additionally, theoretical distributions assume independence of events, which may not hold true in certain situations. It is important for candidates to be aware of these limitations and consider them while interpreting the results obtained from theoretical distributions.
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