Essentials of inferential statistics

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Published 2005 by University Press of America in Lanham, New York .
Written in

Subjects:

• Mathematical statistics.,
• Probabilities.

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Edition Notes

Includes bibliographical references (p. [274]-277).

Statement	Malcolm O. Asadoorian, Demetri Kantarelis.
Contributions	Kantarelis, Demetrius.
Classifications
LC Classifications	QA276 .A83 2005
The Physical Object
Pagination	vii, 286 p. :
Number of Pages	286
ID Numbers
Open Library	OL22627779M
ISBN 10	0761830308
OCLC/WorldCa	57679798

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Essentials of Inferential Statistics by Malcolm O. Asadoorian: An In-Depth Analysis

Inferential statistics is an integral part of the study of mathematical statistics and probabilities. It helps researchers draw conclusions and make predictions about a population based on a sample. One book that delves into the essentials of inferential statistics is "Essentials of Inferential Statistics" by Malcolm O. Asadoorian. Published in 2005, this book serves as an invaluable resource for individuals seeking a comprehensive understanding of inferential statistics.

Understanding the Book: Essentials of Inferential Statistics

"Essentials of Inferential Statistics" is a key reference for any researcher, practitioner, or student interested in gaining a solid foundation in inferential statistics. This book covers the fundamental concepts and techniques used in this field, providing readers with the knowledge and skills necessary to analyze and interpret data effectively.

With its clear and concise explanations, "Essentials of Inferential Statistics" enables readers to grasp complex statistical topics easily. The book presents various statistical tests and procedures, guiding readers through their application and interpretation. It also includes numerous examples and exercises to reinforce learning and enhance comprehension.

Topics Covered in "Essentials of Inferential Statistics"

This book covers a wide range of essential topics related to inferential statistics. Some key areas explored in this book include:

1. Hypothesis testing: Learn how to formulate hypotheses, choose appropriate test statistics, and make decisions based on the results.
2. Confidence intervals: Understand how to construct confidence intervals and interpret them in the context of the population.
3. Regression analysis: Explore the concepts of simple and multiple regression, as well as their practical applications.
4. Analysis of variance: Gain insights into the analysis of variance and its relevance in comparing means between multiple groups or treatments.
5. Non-parametric tests: Discover alternative statistical tests that do not assume specific probability distributions within populations.

The Benefits of "Essentials of Inferential Statistics"

By reading "Essentials of Inferential Statistics," individuals can:

• Develop a solid understanding of inferential statistics and its application in various fields.
• Learn how to analyze and interpret data using appropriate statistical techniques.
• Gain insights into hypothesis testing and confidently make decisions based on statistical results.
• Enhance their research methodology by incorporating inferential statistics effectively.
• Acquire the skills needed to conduct independent statistical analyses and draw meaningful conclusions.

Where to Find and Download "Essentials of Inferential Statistics"

"Essentials of Inferential Statistics" by Malcolm O. Asadoorian can be found on various platforms. To download or read the book online, you can visit legal book download websites specializing in mathematical statistics and probabilities.

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In Summary

"Essentials of Inferential Statistics" by Malcolm O. Asadoorian is an indispensable book for anyone looking to dive into the intricacies of inferential statistics. It covers essential topics and provides readers with the knowledge and skills needed to analyze and interpret data effectively. Whether you are a researcher, practitioner, or student, this book serves as a valuable resource in understanding inferential statistics and its practical application.