MBA Bharathiar University Question Papers, Model Question Papers, Sample Question Papers and Previous Years Question Papers - MBA BU II Year Quantitative Techniques for Management April 2014 Question Paper Free Download
University : Bharathiar University
Course : MBA Administration
Paper Name : Quantitative Techniques for Management
Year of Study : 02, Second, II
Question Paper Code : Not Available
Year of Exam Conduct : April 2014
MBA Degree Examination second year April 2014
Quantitative Techniques for Management
Time: 3 hours
Maximum marks: 100
Answer any five questions. Each question carries 20 marks.
1. What do you understand by a theoretical probability distribution?How it is useful in business decision making?
2. Define a binomial distribution. State the conditions under which binomial probability model is appropriate.
3. What are the parameters of a binomial distribution? Obtain expressions for mean and variance of the binomial variate in terms of these parameters.
4. What is Poisson Process? Obtain probability mass function of Poisson variate as a limiting form of the probability mass function of binomial variate.
5. Obtain mean and standard deviation of a Poisson random variate.
6. How will you use Poisson distribution as an approximation to binomial?
7. Under what conditions will a random variable follow a normal distribution?
8. What is standard normal distribution? Discuss the importance of normal distribution in stastical theory.
University : Bharathiar University
Course : MBA Administration
Paper Name : Quantitative Techniques for Management
Year of Study : 02, Second, II
Question Paper Code : Not Available
Year of Exam Conduct : April 2014
MBA Degree Examination second year April 2014
Quantitative Techniques for Management
Time: 3 hours
Maximum marks: 100
Answer any five questions. Each question carries 20 marks.
1. What do you understand by a theoretical probability distribution?How it is useful in business decision making?
2. Define a binomial distribution. State the conditions under which binomial probability model is appropriate.
3. What are the parameters of a binomial distribution? Obtain expressions for mean and variance of the binomial variate in terms of these parameters.
4. What is Poisson Process? Obtain probability mass function of Poisson variate as a limiting form of the probability mass function of binomial variate.
5. Obtain mean and standard deviation of a Poisson random variate.
6. How will you use Poisson distribution as an approximation to binomial?
7. Under what conditions will a random variable follow a normal distribution?
8. What is standard normal distribution? Discuss the importance of normal distribution in stastical theory.
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