Leon Kaganovskiy

Applied Statistics with Python (eBook, PDF)

Volume I: Introductory Statistics and Regression

• Format: PDF

Produktbeschreibung

Applied Statistics with Python concentrates on applied and computational aspects of statistics, focussing on conceptual understanding and Python-based calculations. It compiles multiple aspects of applied statistics, teaching useful skills in statistics and computational science.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 320
• Erscheinungstermin: 3. März 2025
• Englisch
• ISBN-13: 9781040309971
• Artikelnr.: 72860844

Autorenporträt

Leon Kaganovskiy is an Associate Professor at the Mathematics Department of Touro College. He received a M.S. in Theoretical Physics from Kharkov State University, and M.S. and PhD in Applied Mathematics from the University of Michigan. His most recent interest is in a broad field of Applied Statistics, and he has developed new courses in Bio-Statistics with R, Statistics for Actuaries with R, and Business Analytics with R. He teaches Statistics research courses at the Graduate Program in Speech-Language Pathology at Touro College.

Inhaltsangabe

Preface 1. Introduction 2. Descriptive Data Analysis 3. Probability 4.
Probability Distributions 5. Inferential Statistics and Tests for
Proportions 6. Goodness of Fit and Contingency Tables 7. Inference for
Means 8. Correlation and Regression