| 000 | 03817nam a22005535i 4500 | ||
|---|---|---|---|
| 001 | 978-3-030-56259-5 | ||
| 003 | DE-He213 | ||
| 005 | 20220801220220.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 210208s2021 sz | s |||| 0|eng d | ||
| 020 |
_a9783030562595 _9978-3-030-56259-5 |
||
| 024 | 7 |
_a10.1007/978-3-030-56259-5 _2doi |
|
| 050 | 4 | _aTK5101-5105.9 | |
| 072 | 7 |
_aTJK _2bicssc |
|
| 072 | 7 |
_aTEC041000 _2bisacsh |
|
| 072 | 7 |
_aTJK _2thema |
|
| 082 | 0 | 4 |
_a621.382 _223 |
| 100 | 1 |
_aShankar, P. Mohana. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _948985 |
|
| 245 | 1 | 0 |
_aProbability, Random Variables, and Data Analytics with Engineering Applications _h[electronic resource] / _cby P. Mohana Shankar. |
| 250 | _a1st ed. 2021. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2021. |
|
| 300 |
_aXII, 473 p. 206 illus., 202 illus. in color. _bonline resource. |
||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
||
| 347 |
_atext file _bPDF _2rda |
||
| 505 | 0 | _aChapter 1. Introduction -- Chapter 2. Sets, Venn diagrams, Probability and Bayes’ Rule -- Chapter 3. Concept of a random variable -- Chapter 4. Multiple random variables and their Characteristics -- Chapter 5. Applications to Data Analytics and Modeling. | |
| 520 | _aThis book bridges the gap between theory and applications that currently exist in undergraduate engineering probability textbooks. It offers examples and exercises using data (sets) in addition to traditional analytical and conceptual ones. Conceptual topics such as one and two random variables, transformations, etc. are presented with a focus on applications. Data analytics related portions of the book offer detailed coverage of receiver operating characteristics curves, parametric and nonparametric hypothesis testing, bootstrapping, performance analysis of machine vision and clinical diagnostic systems, and so on. With Excel spreadsheets of data provided, the book offers a balanced mix of traditional topics and data analytics expanding the scope, diversity, and applications of engineering probability. This makes the contents of the book relevant to current and future applications students are likely to encounter in their endeavors after completion of their studies. A full suite of classroom material is included. A solutions manual is available for instructors. Bridges the gap between conceptual topics and data analytics through appropriate examples and exercises; Features 100's of exercises comprising of traditional analytical ones and others based on data sets relevant to machine vision, machine learning and medical diagnostics; Intersperses analytical approaches with computational ones, providing two-level verifications of a majority of examples and exercises. | ||
| 650 | 0 |
_aTelecommunication. _910437 |
|
| 650 | 0 |
_aEngineering mathematics. _93254 |
|
| 650 | 0 |
_aEngineering—Data processing. _931556 |
|
| 650 | 0 |
_aProbabilities. _94604 |
|
| 650 | 0 |
_aStatistics . _931616 |
|
| 650 | 1 | 4 |
_aCommunications Engineering, Networks. _931570 |
| 650 | 2 | 4 |
_aMathematical and Computational Engineering Applications. _931559 |
| 650 | 2 | 4 |
_aProbability Theory. _917950 |
| 650 | 2 | 4 |
_aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. _931790 |
| 710 | 2 |
_aSpringerLink (Online service) _948986 |
|
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030562588 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030562601 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030562618 |
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-56259-5 |
| 912 | _aZDB-2-ENG | ||
| 912 | _aZDB-2-SXE | ||
| 942 | _cEBK | ||
| 999 |
_c78327 _d78327 |
||