Mustafy Tanvir, Rahman Tauhid Ur. Statistics and Data Analysis for Engineers and Scientists

2nd Edition. — Springer Nature, 2024. — 180 p. — ISBN-13: 978-981-99-4660-0.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.Introduction
General Overview
Collection of Data
Measures of Location: The Sample Mean and Median
Other Measures of Locations
Exercises
Measures of Variability
Exercises
Discrete and Continuous Data
Statistical Modeling, Scientific Inspection, and Graphical Diagnostics
Exercises
References
MatLAB
MatLAB
Script Files
Function Files
Arrays and Matrices
Homework Problems
Mathematical Operations
Algebraic Functions
Data Analysis and Statistics
Two-Dimensional Plots
Three-Dimensional Plots
Numerical Analysis
Exercises
Excel
Introduction to Exce
The Fundamentals of Microsoft Excel
Inputting Functions and Formulas
Some Important Mathematical Operations
Trigonometric Functions
Measures of Location and Variation
Correlation and Regression Modeling
Graphs and Charts
Financial Data Analysis
Exercises
SPSS
Introduction to SPSS
Measures of Dispersion
Correlation
Regression Analysis
Graphs and Charts
Inferential Statistics