Statistical Inference (PDF)

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 Chi-Square Statistics, and the Chi-Square 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 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.