"Statistics is a large science having applications in a diverse range of industries. In general, statistics is the process used to collect, analyze, interpret, and derive conclusions from data. In other terms, statistics is the methodology created by scientists and mathematicians for analyzing and inferring meaning from acquired data. Everything remotely related to the collecting, processing, analysis, and presentation of data falls under the area of statistics, as does the meticulous planning that precedes all of these operations. Statistical methods are a critical component of scientific study and development. It aids in the design of experiments, the analysis, and interpretation of findings. Additionally, it assists in making informed judgments in light of the researcher's results. The importance of statistics expertise is not restricted to people seeking employment in their field of study, but extends to all researchers. Statistical science is the capacity to read the results of other researchers and to discriminate between what is good and what is stronger.
The book 'Basic Statistics' contains a detailed and exhaustive examination of statistics. It is organized in such a way that it provides in-depth knowledge of both statistics theory and practice. It elucidates the area's innovative aspects. Which is critical for a comprehensive comprehension of the subject. Additionally, it covers visual data representation, statistical data representation, probability and probability distribution. While acknowledging the long-term implications of the issues, the book makes a point of emphasizing their significance as a contemporary instrument for the discipline's advancement. The book's logical organization of themes, student-friendly language, and copious use of examples make it a useful source of information. This book will be of great assistance to anybody seeking information to further their understanding in this sector.
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"Preface
1. Introduction to Statistics
1.1 Introduction
1.2 What is Statistics?
1.3 Descriptive Versus Inferential Statistics
1.4 Types of Variables and Scales of Measurement
1.5 Statistics In Business Decisions
Exercise
Multiple Choice Questions
Answers
Reference
2. Visual Description of Data
2.1 The Frequency Distribution and the Histogram
2.2 Computer Solutions
2.3 The Stem-and-Leaf Display and the Dot plot
2.4 Other Methods For Visual Representation of The Data
2.5 The Scatter Diagram
2.6 Tabulation and Contingency Tables
Exercise
Multiple Choice Questions
Answers
References
3. Statistical Description of Data
3.1 Statistical Description: Measures of Central tendency
3.2 Statistical Description: Measures of Dispersion
3.3 Descriptive Statistics from Grouped Data
3.4 Statistical Measures of Association
Exercise
Multiple Choice Questions
Answers
References
4. Probability and Probability Distribution
4.1 Fundamental concepts: experiment and event, event and their relationships, conditional and joint probability
4.2 Definitions and classification of probability distribution
4.3 Discrete random variables, expected value and variance
of discrete random variable
4.4 The binomial, Poisson, and hyper geometric probity distributions and their applications
4.5 Continuous Probability distribution: Uniform, Normal, and exponential probability distributions and
their applications
Exercise
Multiple Choice Questions
Answers
References
5. Association Between Variables
5.1 Chi Square Based Measures
5.2 Reduction in Error Measures
Exercise
Multiple Choice Questions
Answers
References
6. Testing of Hypotheses
6.1 Introduction
6.2 The Null and the Alternative Hypothesis
6.3 Some Basic Concepts
6.4 Critical Region in Terms of Test Statistic
6.5 General Testing Procedure
6.6 Tests of Hypotheses about Population Means
6.7 Tests of Hypotheses about Population Proportions
6.8 Tests of Hypotheses about Population Variances
6.9 The Comparison of Two Populations
Exercise
Multiple Choice Questions
Answers
References
Index"
Alfred Pearce is a Visiting Professor at Community College, Prescott. He received his Ph.D. in Statistics from State University, Halifax. He has undertaken academic visits to various institutions has conducted numerous workshops on research methodology, research designs, multivariate analysis, and data modeling in the area of management, social sciences, economics, and health sciences. Pearce has also published numerous articles and book chapters in the field of probability theory, statistical models and priori probability. He has a vast experience in teaching graduate and undergraduate students in the field of probability and statistics. He has also served as a reviewer in several well-known mathematical journals.
