Data Analytics using Python

Mahmoud Ahmad Al-Khasawneh

2024年8月 · Xoffencer international book publication house

关于此电子书

Descriptive statistics are used to identify the fundamental characteristics of data in a research study. Simply summarized information about the sample and measurements is provided. Descriptive statistics provide information about the components and dissemination of values in single or multiple data set concisely. The classical illustrative statistics allow experts to get a quick sense of the central inclination and degree of diffusion of values in a dataset with a single glance. They are useful in gaining an understanding of data distribution as well as in comparing different data distributions, It is frequently necessary for human geographers to take into consideration the locational citations of the data they are working with. Using spatial descriptive statistics, analysts can determine the central propensity and variation of data in a given geographic area or region. The two types of illustrative analysis are mutually supportive of one another. Experts can research the geographic phenomena with which they are involved by combining both statistics and mathematics. Even though descriptive statistics are straightforward concepts in statistical assessment, they are essential and beneficial in today's world of massive amounts of data. The performance and efficacy of descriptive analysis should not be overshadowed in the face of ever-increasing huge quantities of data being generated continuously and distributed via the Internet. Descriptive statistics are characterized by inferential analysis in most cases. When you use descriptive statistics, you are merely explaining what is or what the information reveals about something. When using inferential analysis, you are attempting to draw conclusions that are not based solely on the available data. For example, we use inferential analysis to try to infer what the general public might think based on a sample of data. Alternatively, we use inferential analysis to make decisions about the likelihood that a difference between groups observed in this study is a dependable difference or one that could have occurred by chance. As a result, we use inferential analysis to conclude more general conditions from our data, whereas we use descriptive analysis to simply describe what is happening in our data. Descriptive statistics are used to present quantitative explanations in a manageable format. In a research study, we may have a large number of measures. Alternatively, we can quantify a huge number of participants using any measure. 

作者简介

Mahmoud Ahmad Al-Khasawneh holds a B.Sc. degree in Computer Science from Yarmouk University, Jordan, conferred in 2003. He obtained both his M.Sc. and Ph.D. degrees in Computer Science from University Technology Malaysia (UTM), Johor, Malaysia, in 2013 and 2018, respectively. Currently, he serves as a faculty member in the School of Computing Skyline University College, Sharjah UAE. Dr. Al-Khasawneh's scholarly pursuits span a diverse array of fields within computer science. He has authored numerous papers in esteemed, peer-reviewed journals across leading publishers such as IEEE, Springer, Wiley, Hindawi, and MDPI. His research interests encompass Security, Image Encryption, Wireless Networks, Blockchain, Internet of Things, and Big Data. With a commitment to advancing knowledge and solving contemporary challenges in these domains, he actively engages in research, teaching, and mentorship, contributing to the academic and professional development of his students and peers. Driven by a passion for innovation and a dedication to excellence, he continues to make significant contributions to the field, shaping the future of technology and its applications.