Summary
The command “Let X be …” empowers the mathematical modeller. The use of a single symbol X to represent the main object of interest, and the use of good notation in an analysis, are often a long stride towards the solution. In modelling random phenomena, we may find that X is either naturally the sum of other quantities Y 1,Y 2,…,Y n , or can be conveniently written as such a sum. Especially when the components of this sum are independent, we can take advantage of powerful general results to make meaningful deductions about X.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Bibliography
Box GEP, Muller ME (1958) A note on the generation of random normal deviates. Ann Math Stat 29:610–611
Capiński M, Kopp PE (1999) Measure, integral and probability. SUMS. Springer, Berlin
Harper LH (1967) Stirling behavior is asymptotically normal. Ann Math Stat 38:410–414
Marsaglia G, Bray TA (1964) A convenient method for generating normal variables. SIAM Rev 6(3):260–264
Morgan BJT (1984) Elements of simulation. Chapman and Hall, London
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag London
About this chapter
Cite this chapter
Haigh, J. (2013). Sums of Random Variables. In: Probability Models. Springer Undergraduate Mathematics Series. Springer, London. https://doi.org/10.1007/978-1-4471-5343-6_5
Download citation
DOI: https://doi.org/10.1007/978-1-4471-5343-6_5
Publisher Name: Springer, London
Print ISBN: 978-1-4471-5342-9
Online ISBN: 978-1-4471-5343-6
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)