By U. Narayan Bhat
This introductory textbook is designed for a one-semester path on queueing conception that doesn't require a path in stochastic strategies as a prerequisite. via integrating the mandatory heritage on stochastic procedures with the research of types, this e-book presents a foundational creation to the modeling and research of queueing platforms for a huge interdisciplinary viewers of scholars. Containing routines and examples, this quantity can be used as a textbook by way of first-year graduate and upper-level undergraduate scholars. The paintings can also be precious as a self-study reference for purposes and additional learn.
Read or Download An Introduction to Queueing Theory: Modeling and Analysis in Applications (2nd Edition) PDF
Best statistics books
The following, by means of well known call for, is the up to date version to Joel Best's vintage consultant to knowing how numbers can confuse us. In his new afterword, most sensible makes use of examples from fresh coverage debates to mirror at the demanding situations to bettering statistical literacy. for the reason that its book ten years in the past, Damned Lies and information has emerged because the go-to guide for recognizing undesirable records and studying to imagine significantly approximately those influential numbers.
Das Buch führt in Grundprinzipien der Stichprobenziehung und der zugehörigen statistischen Auswertung ein. Dabei stehen Motivation und anschauliche Beschreibung der Verfahren im Vordergrund. Nach einer generellen Einführung werden sowohl modellbasierte als auch designbasierte Stichprobenverfahren wie Clusterstichprobe und geschichtete Stichprobe entwickelt.
Company facts in perform, 7th variation offers a contemporary, useful and special framework for instructing an introductory direction in enterprise records. The textbook employs real looking examples, carrying on with case stories and a enterprise development subject matter to coach the fabric. The 7th version positive factors extra concise and lucid factors, a higher subject move and a wise use of the easiest and so much compelling examples.
- An introduction to statistical concepts for education and behavioral sciences
- Quantum Statistics of Nonideal Plasmas
- Trends in Private Investment in Developing Countries: Statistics for 1970-96
- Test Equating, Scaling, and Linking: Methods and Practices
- Statistical Distributions
- Statistics in Genetics and in the Environmental Sciences
Additional info for An Introduction to Queueing Theory: Modeling and Analysis in Applications (2nd Edition)
In other words, we are ﬁtting a straight line to the (exam 1, exam 2) pairs in our data. This is done through a classic least-squares method. ) Note that the exam 1 scores, which are stored in the ﬁrst column of our data frame, are collectively referred to as examsquiz[,1]. Omission of the ﬁrst subscript (the row number) means that we are referring to an entire column of the frame. The exam 2 scores are similarly referenced. So, our call to lm() above predicts the second column of examsquiz from the ﬁrst.
3 Introduction to Functions As in most programming languages, the heart of R programming consists of writing functions. A function is a group of instructions that takes inputs, uses them to compute other values, and returns a result. As a simple introduction, let’s deﬁne a function named oddcount(), whose purpose is to count the odd numbers in a vector of integers. Normally, we would compose the function code using a text editor and save it in a ﬁle, but in this quick-and-dirty example, we’ll enter it line by line in R’s interactive mode.
This is typical R. The same is true for this expression, on line 9: mean(abs(pred-x[(k+1):n])) Here, pred contains the predicted values, while x[(k+1):n] has the actual values for the days in question. Subtracting the second from the ﬁrst gives us values of either 0, 1, or −1. Here, 1 or −1 correspond to prediction errors in one direction or the other, predicting 0 when the true value was 1 or vice versa. Taking absolute values with abs(), we have 0s and 1s, the latter corresponding to errors. So we now know where days gave us errors.