Statistical Inference for Everyone
by Brian S Blais
Publisher: Save The Broccoli Publishing 2014
Number of pages: 200
This is a new approach to an introductory statistical inference textbook, motivated by probability theory as logic. It is targeted to the typical Statistics 101 college student, and covers the topics typically covered in the first semester of such a course.
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by Daniel McFadden - University of California, Berkeley
The contents: Economic Analysis and Econometrics; Analysis and Linear Algebra in a Nutshell; Probability Theory in a Nutshell; Limit Theorems in Statistics; Experiments, Sampling, and Statistical Decisions; Estimation; Hypothesis Testing.
by Ryan Martin - University of Illinois at Chicago
Table of contents: Statistics and Sampling Distributions; Point Estimation Basics; Likelihood and Maximum Likelihood Estimation; Sufficiency and Minimum Variance Estimation; Hypothesis Testing; Bayesian Statistic; What Else is There to Learn?
by Henk van Elst - arXiv
These lecture notes were written to provide an accessible though technically solid introduction to the logic of systematical analyses of statistical data to undergraduate and postgraduate students in the Social Sciences and Economics in particular.
The goal of this handbook is to help scientists and engineers incorporate statistical methods in their work as efficiently as possible. Many parts of the book feature case studies or examples with computations from the free downloadable software.