Sampling and descriptive statistics, probability, propagation of error, commonly used distributions, confidence intervals, hypothesis testing, correlation and simple linear regression, multiple regression,... As the main contents of the ebook "Statistics for Engineers and Scientists". Invite you to consult.
(BQ) Part 2 book "Applied numerical methods with MATLAB for engineers and scientists" has contents: Matrix inverse and condition, matrix inverse and condition, eigenvalues, linear regression, polynomial interpolation, numerical integration formulas,...and other contents.
Software requirements for engineering and scientific applications are almost always computational and possess an advanced mathematical component. However, an application that calls for calculating a statistical function, or performs basic differentiation of integration, cannot be easily developed in C++ or most programming languages. In such a case, the engineer or scientist must assume the role of software developer.
(BQ) Part 1 book "Probability and statistics for engineers and scientists" has contents: Introduction to statistics, descriptive statistics, elements of probability, random variables and expectation, special random variables, distributions of sampling statistics, parameter estimation.
(BQ) Part 2 book "Probability and statistics for engineers and scientists" has contents: Hypothesis testing, regression, analysis of variance, goodness of fit tests and categorical data analysis, nonparametric hypothesis tests, quality control, life testing, simulation, bootstrap statistical methods, and permutation tests.
The main reason for a fourth edition of Essential MATLAB for Engineers and
Scientists is to keep up with MATLAB, now in its latest version (7.7 Version
2008B). Like the previous editions, this one presents MATLAB as a problemsolving
tool for professionals in science and engineering, as well as students in
those fields, who have no prior knowledge of computer programming.
Software Solutions for Engineers and Scientists addresses the ever present demand for professionals to develop their own software by supplying them with a toolkit and problem-solving resource for developing computational applications. The authors' provide shortcuts to avoid complications, bearing in mind the technical and mathematical ability of their audience.