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…mehr
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.
Dr. Tanvir Mustafy received his B.Sc. degree in Civil Engineering from BUET, Bangladesh, in 2011, an M.Sc. degree in structural engineering from the University of Alberta, Canada, in 2013, and a Ph.D. Degree in Civil Engineering (Computational Mechanics) from Ecole Polytechnique of Montreal, Canada, in 2019. His research and teaching interests include the theory and application of machine learning, structural engineering, earthquake engineering, advanced finite element modeling, dynamics of structures, data analysis, and injury biomechanics. Dr. Mustafy currently serves as an Associate Professor in the Department of Civil Engineering at the Military Institute of Science and Technology (MIST), Bangladesh. Before joining MIST, Dr. Mustafy worked as a member of a prestigious scientist group led by one of the most renowned Research Chairs in Canada during his doctoral period. He traveled to France as a visiting scholar and spent three months working at Aix-Marseille University. Dr. Mustafy also received the prestigious Professional Structural Engineer (SEng) by BUET, ICC (USA), RAJUK, URP and IEB in 2023. Dr. Tauhid Rahman finished his Ph.D. in Environmental Engineering from Tohoku University, Japan, in 2009. He did his M.Sc. in Environmental Engineering, Land, and Water Engineering from KTH, Sweden, and his B.Sc. in Civil Engineering from Bangladesh University of Engineering and Technology, Bangladesh. He is currently working as a professor in the CE Department of MIST. His research interests are water quality modeling, land use change detection, climate change, water insecurity, micro-climate effect, etc.
Inhaltsangabe
General Overview.- Introduction to MATLAB.- The Fundamentals of Microsoft Excel.- Introduction to SPSS.
