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Mathematical statistics --- Data processing --- Congresses --- Mathematical statistics - Data processing - Congresses

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Step-by-Step Basic Statistics Using SAS: Student Guide first introduces you to SAS software, then leads you through a variety of elementary statistical analyses that are commonly used in the social and behavioral sciences. With SAS, you can focus more on conceptual issues in statistical analysis and less on the mechanics of performing mathematical operations by hand. Main topics include how to use the SAS windowing environment to write and submit SAS programs how to create SAS data sets and modify the variables that they contain basic descriptive statistics (measures of central tendency and variability, frequency tables, and graphs) correlation and regression t tests (single-sample, independent and paired samples) analysis of variance (ANOVA), both one-way and factorial the chi-square test of independence. Even if you are new to statistics and computers, you soon will be recording research data, writing SAS programs, and interpreting the results. Reinforce what you've learned by completing the exercises in the companion text, Step-by-Step Basic Statistics Using SAS: Exercises. Check your accuracy with the solutions and analysis reports that are provided

QA 276.4 Mathematical statistics. Data processing --- SAS

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Data Science, Big Data, Artificial Intelligence and Generative AI are currently some of the most talked-about concepts in industry, government, and society, and yet also the most misunderstood. This book will clarify these concepts and provide you with practical knowledge to apply them:- Understand crucial data science concepts, from statistics and mathematics to legal and ethical considerations.- Learn how to build data platforms and deploy safe and robust data projects to production.- Gain the vocabulary to communicate technical requirements and roadmaps to diverse business stakeholders.- Dive into practical case studies that illustrate how knowledge generated from data is changing various industries over the long term.

Automatic Data Processing --- Automatic Data Processing --- Automatic Data Processing --- Data analysis --- QA 276.4 Mathematical statistics. Data processing --- QA 276.4 Mathematical statistics. Data processing --- QA 276.4 Mathematical statistics. Data processing

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Mathematical statistics --- Linear models (Statistics) --- Multivariate analysis --- Data processing --- Mathematical statistics - Data processing

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This is an introductory applied statistics text that can be used for a one- or two-semester course at either the undergraduate or graduate level. Central features are its hands-on approach; the use of real data; the wealth of exercises and illustrated examples using these data; the complete set of detailed answers to exercises in an appendix; the presentation of statistical methods with a clear, conceptual emphasis that includes an historical account of each method; and the integration of SPSS in a way that reflects statistical practice. Step-by-step instructions for using SPSS are provided as each new analytic procedure is introduced. A data CD is included with the text so that students may conduct their own statistical analyses and learn firsthand how statistics is used in practice.

Mathematical statistics --- Data processing --- SPSS (Computer file) --- Mathematical statistics - Data processing