A textbook in statistics should be written to such a standard that it does what it claims on the cover i.e. it should teach statistics. Undergraduate students who use other textbooks to study statistics typically find themselves lost within minutes or even seconds! What's the point of buying such a textbook if it doesn't teach? This was the inspiration for writing this textbook. The objective was to write a textbook that enables a student to learn statistics from a book. This book achieves that objective!
Learning statistics is easy if the material is presented well. This book adopts a step by step approach to learning statistics. The approach is non-theoretical and the material is taught through worked examples. The writing style is exciting and fresh and reflects the authors' style of teaching. A companion website is also provided which includes the following:
- A step by step guide in the use of the computer software packages Minitab, SPSS and Excel.
- Complete solutions to all odd numbered questions in the book.
The book represents the finished product of ten years of work. To investigate it's worth it has been tested on different groups of students. Students were asked to read certain sections/chapters and to put their hands up if they experienced difficulties in understanding the material. No hands were raised! When the students had completed a section they were asked to answer the questions at the end of that section. This is the true acid test for any book. The results - approximately 92% of students answered the questions correctly while the other 8% made small/silly mistakes. This book "does what it says on the tin" i.e. it teaches statistics. Irrespective of your college discipline, be it statistics, biostatistics, medicine, mathematics, business, economics, engineering, science, psychology etc. this book is a must for a student studying a first/intermediate course in statistics.
|Publisher:||Algebra Publishing Higher Education|
|Product dimensions:||8.00(w) x 10.88(h) x 1.88(d)|
Table of Contents
Chapter 1 Tabular and Graphical Techniques used to Describe Data 1 1.1 Data 2 1.2 Summarizing Qualitative Data 5 1.3 Summarizing Quantitative Data 10 1.4 Stem and Leaf Plot 20 1.5 Scatter Diagrams 27 1.6 Chapter 1 Exercises 31 Chapter 2 Numerical Techniques used to Describe Data 35 2.1 Measures of Location 36 2.2 Measures of Relative Position 41 2.3 Measures of Variability 50 2.4 Exploratory Data Analysis 61 2.5 Correlation 66 2.6 Summary Measures for Grouped Data 75 2.7 Chapter 2 Exercises 81 Chapter 3 Probability 87 3.1 Counting 85 3.2 Permutations 88 3.3 Combinations 92 3.4 Probability 99 3.5 Rules of Probability 101 3.6 Complements 109 3.7 Conditional Probability 111 3.8 Independent Events 116 3.9 Multiplication Law 117 3.10 Bayes Theorem 124 3.11 Chapter 3 Exercises 145 Chapter 4 Discrete Random Variables and Probability Distributions 150 4.1 Random variable 149 4.2 Probability Distribution 152 4.3 Expected Value and Variance 156 4.4 The Binomial Distribution 164 4.5 The Poisson Probability Distribution 186 4.6 The Hypergeometric Probability Distribution 196 4.7 The Multinomial Probability Distribution 212 4.8 Chapter 4 Exercises 216 Chapter 5 Continuous Random Variables and Probability Distributions 220 5.1 Continuous Distributions 220 5.2 The Normal Probability Distribution 222 5.3 The Exponential Probability Distribution 271 5.4 Chapter 5 Exercises 282 Chapter 6 Sampling and Sampling Distributions 285 6.1 Sampling and Sampling Distributions 285 6.2 Simple Random Sampling 285 6.3 Point Estimation 287 6.4 Sampling Distributions 293