Mathematics

Mastering Quantitative Techniques
A Comprehensive Guide to Data Analysis and Interpretation

Editors: Dr. Amir Ahmad Dar
Dr. Mohammad Shahfaraz Khan
Dr. Naushad Alam
Olayan Albalawi

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Mastering Quantitative Techniques

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Pub Date: TBA
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Short description of the Book:

Mastering Quantitative Techniques is a comprehensive and in-depth guide that delves into the world of data analysis and interpretation. This book equips readers with the necessary knowledge and practical skills to confidently conduct quantitative research, analyze complex datasets, and make data-driven decisions. Covering a wide range of quantitative methods and statistical tools, this guide provides clear explanations, illustrative examples, and hands-on exercises to facilitate learning and understanding. The impact of Mastering Quantitative Techniques is multifaceted. It empowers students, researchers, and professionals across various disciplines with the ability to conduct rigorous data analysis independently. By breaking down complex statistical concepts into manageable components, the book fosters confidence and competence in handling quantitative data, thereby enhancing the quality and validity of research outcomes.

As editors, we shall endeavor to create a book that explores the applied and empirical facets of data analysis rather than their theoretical descriptions.

Coverage:

We request potential authors to consider submitting their scholarly findings to enrich the content of this intended book. The book will cover the following topics, but not limited to:

  • Introduction to Quantitative Research: Understanding the Basics
  • Descriptive Statistics: Summarizing and Visualizing Data
  • Probability Distributions: Understanding the Foundation of Statistical Inference
  • Hypothesis Testing: Making Inferences from Sample Data
  • Confidence Intervals: Estimating Population Parameters with Precision
  • Correlation and Regression Analysis: Examining Relationships between Variables
  • ANOVA (Analysis of Variance): Comparing Multiple Group Means
  • Chi-Square Analysis: Investigating Categorical Data Relationships
  • Time Series Analysis: Understanding Temporal Patterns and Trends
  • Sampling Techniques: Ensuring Representative Data Collection
  • Experimental Design: Controlling for Confounding Factors
  • Factor Analysis: Identifying Underlying Factors in Complex Data
  • Structural Equation Modeling: Examining Complex Relationships in Data
  • Bayesian Statistics: Incorporating Prior Knowledge into Analysis
  • ARMA, AR, MA, AIRMA, Computing
  • Actuarial Sciences


Important Dates:

Initial Proposal / Abstract Submission (400 - 600 words)

Deadline: June 10th, 2024

Notification of Acceptance: July 20th, 2024

Full Chapter (8,000 - 10,000 words) Submission Due: On or before September 10th , 2024


Submission procedure:

Researchers and practitioners are invited to submit a one-page chapter proposal or abstract on or before June 10th, 2024, clearly mentioning the title of the paper and author(s) details. Author(s) will be notified about the status of their proposals by July 20th, 2024. Full chapters (15-30 pages) are expected to be submitted by September 10th, 2024. All submitted chapters will be peer-reviewed.

Prospective authors are requested to submit their proposals/ full-length chapters as an email attachment in a Word file to:


Authors must refer to the following link for detailed guidelines for chapter preparation: http://www.appleacademicpress.com/publishwithus

Note: There is no publication fee for manuscripts submitted to this book publication. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere.


About the Authors / Editors:
Editors: Dr. Amir Ahmad Dar
Assistant Professor, Department of Statistics, Lovely Professional University, Punjab, India Email: amirphd111@gmail.com


Dr. Mohammad Shahfaraz Khan
Assistant Professor, University of Technology and Applied Sciences, Salalah, Oman Email: mskhan@utas.edu.om


Dr. Naushad Alam
Assistant Professor, Dhofar University, Oman. Email: nalam@du.edu.om


Olayan Albalawi
Faculty of Science, University of Tabuk, Saudi Arabia Email: oalbalwi@ut.edu.sa





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