Del i serien Statistics for Industry, Technology, and Engineering

Modern Statistics

A Computer-Based Approach with Python

Häftad, Engelska, 2023

AvRon S. Kenett,Shelemyahu Zacks,Peter Gedeck

1 119 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

Finns i fler format (1)

Inbunden

1 529 kr

Skickas inom 10-15 vardagar

It covers topics such as statistical process control, including multivariate methods, the design of experiments, including computerexperiments and reliability methods, including Bayesian reliability.

Produktinformation

Utgivningsdatum2023-09-22
Mått155 x 235 x 25 mm
Vikt698 g
FormatHäftad
SpråkEngelska
SerieStatistics for Industry, Technology, and Engineering
Antal sidor438
FörlagBirkhauser Verlag AG
ISBN9783031075681

Tillhör följande kategorier

Matematisk statistik inom Naturvetenskap och teknik
Maskinteknik och material inom Naturvetenskap och teknik
Affärsapplikationer inom Data och IT
Databaser inom Data och IT

Professor Ron Kenett is Chairman of the KPA Group, Israel and Senior Research Fellow at the Samuel Neaman Institute, Technion, Haifa Israel and Professor, University of Turin, Italy. He is an applied statistician combining expertise in academic, consulting and business domains.Shelemyahu Zacks is a Distinguished Professor emeritus in the Mathematical Sciences department of Binghamton University.He is a Fellow of the IMS, ASA, AAAS and an elected member of the ISI. Professor Zacks has published eleven books and more than 170 journal articles on subjects of design of experiments, statistical process control, statistical decision theory, sequential analysis, reliability and sampling from finite populations. Professor Zacks served as an Editor and Associate Editor of several Statistics and Probability journals.Dr. Peter Gedeck, a Senior Data Scientist at Collaborative Drug Discovery, specializes in the development of machine learning algorithms to predict biological and physicochemical properties of drug candidates. In addition, he teaches data science at the University of Virginia and at statistics.com.

Analyzing Variability: Descriptive Statistics.- Probability Models and Distribution Functions.- Statistical Inference and Bootstrapping.- Variability in Several Dimensions and Regression Models.- Sampling for Estimation of Finite Population Quantities.- Time Series Analysis and Prediction.- Modern analytic methods: Part I.- Modern analytic methods: Part II.- Introduction to Python.- List of Python packages.- Code Repository and Solution Manual.- Bibliography.- Index.