Articles by "Statistics"

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Tanvir Mustafy, Tauhid Rahman - 281 pages - Language: ‎English - Publisher: ‎Springer; (January, 2024).

This textbook summarizes the different statistical, scientific, and financial data analysis methods for users ranging from a high school level to a professional level. It aims to combine the data analysis methods using three different programs - Microsoft Excel, SPSS, and MATLAB. The book combining the different data analysis tools is a unique approach. The book presents a variety of real-life problems in data analysis and machine learning, delivering the best solution. Analysis methods presented in this book include but are not limited to, performing various algebraic and trigonometric operations, regression modeling, and correlation, as well as plotting graphs and charts to represent the results. Fundamental concepts of applied statistics are also explained here, with illustrative examples. Thus, this book presents a pioneering solution to help a wide range of students, researchers, and professionals learn data processing, interpret different findings derived from the analyses,and apply them to their research or professional fields.

The book also includes worked examples of practical problems. The primary focus behind designing these examples is understanding the concepts of data analysis and how it can solve problems. The chapters include practice exercises to assist users in enhancing their skills to execute statistical analysis calculations using software instead of relying on tables for probabilities and percentiles in the present world.

William Navidi - 960 pages - Language: English - Publisher: ‎ McGraw-Hill; 6th Edition (January, 2023).

Statistics for Engineers and Scientists stands out for its clear presentation of applied statistics. The book takes a practical approach to methods of statistical modeling and data analysis that are most often used in scientific work. 

This edition features a unique approach highlighted by an engaging writing style that explains difficult concepts clearly, along with the use of contemporary real world data sets, to help motivate students and show direct connections to industry and research. While focusing on practical applications of statistics, the text makes extensive use of examples to motivate fundamental concepts and to develop intuition.

Table of Contents: Chapter 1: Sampling and Descriptive Statistics - Chapter 2: Probability - Chapter 3: Propagation of Error - Chapter 4: Commonly Used Distributions - Chapter 5: Confidence Intervals - Chapter 6: Hypothesis Testing - Chapter 7: Correlation and Simple Linear Regression - Chapter 8: Multiple Regression - Chapter 9: Factorial Experiments - Chapter 10: Statistical Quality Control.

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