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Subrat SaurabhAuthor of Kuch Woh Pal
Now a day’s software industry is very strong and interconnected with other industries. Its role and involvement is high. Without software systems nothing is possible. For the last few decades onwards the embedding software into hardware components is relatively high. All most all kinds of problems are being tackled by software industry. Once upon a time software development was very small and small in nature but cost of the software project was vast. But
Now a day’s software industry is very strong and interconnected with other industries. Its role and involvement is high. Without software systems nothing is possible. For the last few decades onwards the embedding software into hardware components is relatively high. All most all kinds of problems are being tackled by software industry. Once upon a time software development was very small and small in nature but cost of the software project was vast. But, things are changed like anything now the common man can reach to solve their problems. In this context, and huge demand in the industry and healthy competition software industry has to quote exact figures on the product.
A Software Project is dynamic. The code changes, the design changes, and the requirements change. What’s more, changes in the requirements lead to more changes in the design and changes in the design lead to even more changes in the code and test cases. But the estimation process is static. If the software cost is underestimated, inefficiencies will be brought to the project and the actual cost will be surely increased. Overestimated software costs will lose the bid, waste the time, money, staff, and other resources, and lead to financial loss, even economic failure of the organization. Therefore, the ability to accurately estimate the software cost needed to complete the project on time is crucial for software organizations.
Statistics for Engineers with R Programming is a textbook for advanced undergraduate and graduate students from a variety of disciplines. The book is a composition of R concepts followed by the usage of R in statistics. It is intended to prepare students to deal with solving statistical problems using R programming beyond the classroom and university settings. We presume students using this book have a minimal mathematical background (high school algebra) and
Statistics for Engineers with R Programming is a textbook for advanced undergraduate and graduate students from a variety of disciplines. The book is a composition of R concepts followed by the usage of R in statistics. It is intended to prepare students to deal with solving statistical problems using R programming beyond the classroom and university settings. We presume students using this book have a minimal mathematical background (high school algebra) and no prior coursework in statistics. The first eight chapters cover the basic concepts of R programming. Chapters nine to eighteen deal with statistical concepts using R. The last three chapters provided case studies that explore the concept of statistics to problems of a very practical nature.
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