03841nam a22005775i 4500 978-981-99-4661-7 DE-He213 20251030110918.0 cr nn 008mamaa 240110s2024 si | s |||| 0|eng d 9789819946617 978-981-99-4661-7 10.1007/978-981-99-4661-7 doi Q342 UYQ bicssc COM004000 bisacsh UYQ thema Mustafy, Tanvir. author. aut http://id.loc.gov/vocabulary/relators/aut 69427 Statistics and Data Analysis for Engineers and Scientists [electronic resource] / by Tanvir Mustafy, Md. Tauhid Ur Rahman. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. IX, 180 p. 259 illus., 230 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Transactions on Computer Systems and Networks, 2730-7492 General Overview -- Introduction to MATLAB -- The Fundamentals of Microsoft Excel -- Introduction to SPSS. 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. . Computational intelligence. 64052 Quantitative research. Mathematical statistics Data processing. 64750 Engineering Data processing. Computational Intelligence. 64052 Data Analysis and Big Data. Statistics and Computing. 66446 Data Engineering. 66059 Rahman, Md. Tauhid Ur. author. aut http://id.loc.gov/vocabulary/relators/aut 69428 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819946600 Printed edition: 9789819946624 Printed edition: 9789819946631 Transactions on Computer Systems and Networks, 2730-7492 67020 https://doi.org/10.1007/978-981-99-4661-7 ZDB-2-INR ZDB-2-SXIT 57157 57157