Ris a language and environment for statistical computing and graphics. it is a gnu project which is similar to the s language and environment which was developed at bell laboratories (formerly at& t, now lucent technologies) by john chambers and colleagues. r can be considered as a different implementation of s. there are some important differences, but much code written for s runs unaltered under r. why are statistical programming languages important to data scientists? what are some advantages and disadvantages the r programming language has over the other main statistical programming languages (i. e. python, sas, sql)?

Solution: the categorization of functional and non-functional requirement are as follows: some of the more typical functional requirements include: • business rules• transaction corrections, adjustments and cancellations• administrative functions• authentication• authorization levels• audit tracking• external interfaces• certification requirements• reporting requirements• historical data• legal or regulatory requirementswhile,some typical non-functional requirements are: • performance – for example response time, throughput, utilization, static volumetric• scalability• capacity• availability• reliability• recoverability• maintainability• serviceability• security• regulatory• manageability• environmental• data integrity• usability• interoperability

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