Book description
A concise, easily accessible introduction to descriptive and inferential techniques
Statistical Inference: A Short Course offers a concise presentation of the essentials of basic statistics for readers seeking to acquire a working knowledge of statistical concepts, measures, and procedures.
The author conducts tests on the assumption of randomness and normality, provides nonparametric methods when parametric approaches might not work. The book also explores how to determine a confidence interval for a population median while also providing coverage of ratio estimation, randomness, and causality. To ensure a thorough understanding of all key concepts, Statistical Inference provides numerous examples and solutions along with complete and precise answers to many fundamental questions, including:
How do we determine that a given dataset is actually a random sample?
With what level of precision and reliability can a population sample be estimated?
How are probabilities determined and are they the same thing as odds?
How can we predict the level of one variable from that of another?
What is the strength of the relationship between two variables?
The book is organized to present fundamental statistical concepts first, with later chapters exploring more advanced topics and additional statistical tests such as Distributional Hypotheses, Multinomial ChiSquare Statistics, and the ChiSquare Distribution. Each chapter includes appendices and exercises, allowing readers to test their comprehension of the presented material.
Statistical Inference: A Short Course is an excellent book for courses on probability, mathematical statistics, and statistical inference at the upperundergraduate and graduate levels. The book also serves as a valuable reference for researchers and practitioners who would like to develop further insights into essential statistical tools.
Table of contents
 Cover
 Title Page
 Copyright
 Dedication
 Preface
 Chapter 1: The Nature of Statistics
 Chapter 2: Analyzing Quantitative Data

Chapter 3: Descriptive Characteristics of Quantitative Data
 3.1 The Search for Summary Characteristics
 3.2 The Arithmetic Mean
 3.3 The Median
 3.4 The Mode
 3.5 The Range
 3.6 The Standard Deviation
 3.7 Relative Variation
 3.8 Skewness
 3.9 Quantiles
 3.10 Kurtosis
 3.11 Detection of Outliers
 3.12 So What do We do with All this Stuff?
 Exercises
 Appendix 3.A Descriptive Characteristics of Grouped Data
 Chapter 4: Essentials of Probability
 Chapter 5: Discrete Probability Distributions And Their Properties
 Chapter 6: The Normal Distribution

Chapter 7: Simple Random Sampling and the Sampling Distribution of the Mean
 7.1 Simple Random Sampling
 7.2 The Sampling Distribution of The Mean
 7.3 Comments on the Sampling Distribution of the Mean
 7.4 A Central Limit Theorem
 Exercises
 Appendix 7.A Using a Table of Random Numbers
 Appendix 7.B Assessing Normality Via the Normal probability Plot
 Appendix 7.C Randomness, Risk, and Uncertainty
 Chapter 8: Confidence Interval Estimation Of μ
 Chapter 9: The Sampling Distribution of a Proportion and Its Confidence Interval Estimation

Chapter 10: Testing Statistical Hypotheses
 10.1 What is a Statistical Hypothesis?
 10.2 Errors in Testing
 10.3 The Contextual Framework of Hypothesis Testing
 10.4 Selecting A Test Statistic
 10.5 The Classical Approach to Hypothesis Testing
 10.6 Types of Hypothesis Tests
 10.7 Hypothesis Tests for μ (σ Known)
 10.8 Hypothesis Tests for μ (σ Unknown And n Small)
 10.9 Reporting The Results of Statistical Hypothesis Tests
 10.10 Hypothesis Tests for The Population Proportion (of Successes) p
 Exercises
 Appendix 10.A Assessing The Randomness of A Sample
 Appendix 10.B Wilcoxon Signed Rank Test (of a Median)
 Appendix 10.C Lilliefors GoodnessofFit Test for Normality

Chapter 11: Comparing Two Population Means and Two Population Proportions
 11.1 Confidence Intervals for the Difference of Means when Sampling from Two Independent Normal Populations
 11.2 Confidence Intervals for the Difference of Means When Sampling from Two Dependent Populations: Paired Comparisons
 11.3 Confidence Intervals for the Difference of Proportions When Sampling from Two Independent Binomial Populations
 11.4 Statistical Hypothesis Tests for the Difference of Means When Sampling from Two Independent Normal Populations
 11.5 Hypothesis Tests for the Difference of Means When Sampling From Two Dependent Populations: Paired Comparisons
 11.6 Hypothesis Tests for the Difference of Proportions when Sampling from Two Independent Binomial Populations
 Exercises
 Appendix 11.A Runs Test for Two Independent Samples
 Appendix 11.B Mann–Whitney (Rank Sum) Test for Two Independent Populations
 Appendix 11.C Wilcoxon Signed Rank Test When Sampling from Two Dependent Populations: Paired Comparisons

Chapter 12: Bivariate Regression and Correlation
 12.1 Introducing an Additional Dimension to our Statistical Analysis
 12.2 Linear Relationships
 12.3 Estimating the Slope and Intercept of the Population Regression Line
 12.4 Decomposition of the Sample Variation in Y
 12.5 Mean, Variance, and Sampling Distribution of the Least Squares Estimators β and β
 12.6 Confidence Intervals for β and β
 12.7 Testing Hypotheses about β and β
 12.8 Predicting the Average Value of Y given X
 12.9 The Prediction of a Particular Value of Y given X
 12.10 Correlation Analysis
 Exercises
 Appendix 12.A Assessing Normality (Appendix 7.B Continued)
 Appendix 12.B On Making Causal Inferences

Chapter 13: An Assortment of Additional Statistical Tests
 13.1 Distributional Hypotheses
 13.2 The Multinomial ChiSquare Statistic
 13.3 The ChiSquare Distribution
 13.4 Testing Goodness Of Fit
 13.5 Testing Independence
 13.6 Testing k Proportions
 13.7 A Measure of Strength of Association in a Contingency Table
 13.8 A Confidence Interval for σ2 Under Random Sampling from a Normal Population
 13.9 The F Distribution
 13.10 Applications of the F Statistic to Regression Analysis
 Exercises
 Appendix A
 Solutions to Exercises
 References
 Index
Product information
 Title: Statistical Inference: A Short Course
 Author(s):
 Release date: July 2012
 Publisher(s): Wiley
 ISBN: 9781118229408
You might also like
book
Spark: The Definitive Guide
Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the …
book
Programming Rust, 2nd Edition
The Rust programming language offers the rare and valuable combination of statically verified memory safety and …
book
Fluent Python, 2nd Edition
Python’s simplicity lets you become productive quickly, but often this means you aren’t using everything it …
book
Fluent Python
Python’s simplicity lets you become productive quickly, but this often means you aren’t using everything it …