HomeUnitext for IInd Year: Introduction to Statistics
Unitext for IInd Year: Introduction to Statistics
Editor: Luna Cole
Year: 2023
Binding: Hardback
Price: £ 250.00
"During the 17th to 18th century, “Statistics” had gradually developed, and a lot of work was completed and announced at the end of the 19th century. Sir Ronald Fisher, one of the fathers of modern statistics, showed how statistics can be used to analyze very complicated data sets, and developed many of the methods that we still use today. He also founded the Rothamsted Statistics Department where Genstat was first developed. Today, statistics are integrated into science, engineering, agriculture, medicine, the arts and other diverse fields of study. Statistics is a process to convert data into a set of equations that can help us solve problems. This science can help us understand our past and make predictions about the future. Using statistics, we can analyze data in different fields to monitor changing patterns, then use this analysis to draw conclusions and make forecasts. Statistics is the set of mathematical equations that we used to analyze the things. It keeps us informed about, what is happening in the world around us. Statistics is important because today we live in the information world and much of this information’s are determined mathematically by statistics help. It means to be informed correct data and statics concepts are necessary.
This book includes displaying and describing data, the normal curve, regression, probability, statistical inference, confidence intervals, and hypothesis tests with applications in the real world. The book teaches you statistical thinking concepts that are essential for learning from data and communicating insights. You will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts. There is data abound in this information age; how to extract useful knowledge and gain a sound understanding of complex data sets has been more of a challenge. In this book, we will focus on the fundamentals of statistics, which may be broadly described as the techniques to collect, clarify, summarize, organize, analyze, and interpret numerical information. You will gain the foundational skills that prepare you to pursue more advanced topics in statistical thinking and machine learning. Statistical knowledge helps you use the proper methods to collect the data, employ the correct analyses, and effectively present the results. Statistics is a crucial process behind how we make discoveries in science, make decisions based on data, and make predictions. Statistics allows you to understand a subject much more deeply."
"Preface
Chapter 1 Introduction
1.1 Definition of Statistics
1.2 Classification of Statistics
1.3 Applications of Statistics
Chapter 2 Sampling Theory
2.1 Basic Concepts of Sampling Theory
2.2 Reasons for Sampling
2.3 A Review of Methods of Sampling (Probability vs
Non-Probability Sampling Techniques)
Chapter 3 Data Collection and Presentation
3.1 Data Collection
3.2 Data and Types of Data
3.3 Data Collection Methods
3.4 Tabular Methods of Data Presentation
3.5 Frequency Distribution
3.6 Graphic Methods of Data Presentation
Chapter 4 Measures of Central Tendency
4.1 Measures of Central Tendency Definition
4.2 The Use of Summation Notation
4.3 The Mean and Its Properties
4.4 Arithmetic, Geometric, and Harmonic
4.5 The Median and Other Measures of Location
Chapter 5 Measure of Variation
5.1 Introduction to Measure of Variation
5.2 Types of Measures of Variation
5.3 Moments, Skewness and Kurtosis
Chapter 6 Simple Linear Regression and Correlation
6.1 Simple Linear Regression
6.2 The Model behind Linear Regression
6.3 Interpreting Regression Coefficients
6.4 Robustness of Simple Linear Regression
6.5 Correlation
Chapter 7 Elementary Probability
7.1 Definition of Terms and Concepts
7.2 Principles of Counting
7.3 Some Rules of Probability
7.4 Conditional and Independent Probabilities
7.5 Basic Concepts of Probability Distributions
INDEX"
Luna Cole served as a Professor of Statistics at the Institute for Statistics and Econometrics, Sussex. She taught Statistics, Computational Statistics and Generalized Linear Models. Her research focused on multivariate statistics, macroeconomics, international economics, mathematical modeling, computational statistics and generalized linear models. Cole has published many papers in local and international peer-reviewed journals in these fields, and has also published books about electoral systems and applications of MATLAB in social sciences.
