In which of the following practical situations, Poisson Distribution can be used?

A. Number of customers arriving at the super markets per hour.

B. Number of typographical errors per page in a typed material.

C. Number of accidents taking place per day on a busy road.

D. Dice throwing problems.

E. Number of defective material say, blades, etc. in a packing manufactured by a good concern.

Choose the most appropriate answer from the options given below:

The correct answer is A, B, C and E only.

Key PointsThe correct answer is: 

A. Number of customers arriving at the supermarkets per hour: This situation involves events occurring randomly in time (customers arriving) at a constant average rate (per hour), making it suitable for modeling with a Poisson distribution.

B. Number of typographical errors per page in a type material:      Typographical errors can occur randomly and independently on each page, which aligns with the characteristics of a Poisson distribution.

C. Number of accidents taking place per day on a busy road:  While the Poisson distribution assumes a constant average rate of events occurring over a specified interval, the number of accidents on a busy road may vary based on several factors. In this case, it might be more appropriate to consider other distributions, such as the Negative Binomial distribution, to account for overdispersion.

E. Number of defective materials in a packing manufactured by a good concern: Defects in manufactured items can be seen as random and independent events, making the Poisson distribution suitable for modeling the number of defective materials.

Hence, The correct answer is A, B, C and E only