Statistical Inference

<p><b><i>A concise, easily accessible introduction to descriptive and inferential techniques</i></b></p> <p><i>Statistical Inference: A Short Course</i> offers a concise presentation of the essentials of basic statistics for readers seeking to acquire a working knowledge of statistical concepts, measures, and procedures.</p> <p>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, <i>Statistical Inference</i> provides numerous examples and solutions along with complete and precise answers to many fundamental questions, including:</p> <ul> <li>How do we determine that a given dataset is actually a random sample?</li> <li>With what level of precision and reliability can a population sample be estimated?</li> <li>How are probabilities determined and are they the same thing as odds?</li> <li>How can we predict the level of one variable from that of another?</li> <li>What is the strength of the relationship between two variables?</li> </ul> <p>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 Chi-Square Statistics, and the Chi-Square Distribution. Each chapter includes appendices and exercises, allowing readers to test their comprehension of the presented material.</p> <p><i>Statistical Inference: A Short Course</i> is an excellent book for courses on probability, mathematical statistics, and statistical inference at the upper-undergraduate 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.</p>