Hahs-Vaughn D.L., Lomax R.G. Statistical Concepts. A First Course

4th ed. — Routledge, 2020. — 461 p. — ISBN: 0367203960, 9780367203962.Statistical Concepts--A First Course presents the first 10 chapters from An Introduction to Statistical Concepts, Fourth Edition. Designed for first and lower-level statistics courses, this book communicates a conceptual, intuitive understanding of statistics that does not assume extensive or recent training in mathematics and only requires a rudimentary knowledge of algebra.
Covering the most basic statistical concepts, this book is designed to help readers really understand statistical concepts, in what situations they can be applied, and how to apply them to data. Specifically, the text covers basic descriptive statistics, including ways of representing data graphically, statistical measures that describe a set of data, the normal distribution and other types of standard scores, and an introduction to probability and sampling. The remainder of the text covers various inferential tests, including those involving tests of means (e.g., t tests), proportions, variances, and correlations. In addition to instructions and screen shots for using SPSS, new to this edition is annotated script for using R.
Providing accessible and comprehensive coverage of topics suitable for an undergraduate or graduate course in statistics, this book is an invaluable resource for students undertaking an introductory course in statistics in any number of social science and behavioral science disciplines.DedicationWhat Is the Value of Statistics?
Brief Introduction to the History of Statistics
General Statistical Definitions
Types of Variables
Scales of Measurement
Additional Resources
Problems
Data Representation
Tabular Display of Distributions
Graphical Display of Distributions
Percentiles
Recommendations Based on Measurement Scale
Computing Tables, Graphs, and More Using SPSS
Computing Tables, Graphs, and More Using R
Research Question Template and Example Write-Up
Additional Resources
Problems
Univariate Population Parameters and Sample Statistics
Summation Notation
Measures of Central Tendency
Measures of Dispersion
Computing Sample Statistics Using SPSS
Computing Sample Statistics Using R
Research Question Template and Example Write-Up
Additional Resources
Problems
The Normal Distribution and Standard Scores
The Normal Distribution and How It Works
Standard Scores and How They Work
Skewness and Kurtosis Statistics
Computing Graphs and Standard Scores Using SPSS
Computing Graphs and Standard Scores Using R
Research Question Template and Example Write-Up
Additional Resources
Problems
Introduction to Probability and Sample Statistics
Brief Introduction to Probability
Sampling and Estimation
Additional Resources
Problems
Introduction to Hypothesis Testing: Inferences About a Single Mean
Inferences About a Single Mean and How They Work
Computing Inferences About a Single Mean Using SPSS
Computing Inferences About a Single Mean Using R
Data Screening
Power Using G*Power
Research Question Template and Example Write-Up
Additional Resources
Problems
Inferences About the Difference Between Two Means
Inferences About Two Independent Means and How They Work
Inferences About Two Dependent Means and How They Work
Computing Inferences About Two Independent Means Using SPSS
Computing Inferences About Two Dependent Means Using SPSS
Computing Inferences About Two Independent Means Using R
Computing Inferences About Two Dependent Means Using R
Data Screening
G*Power
Research Question Template and Example Write-Up
Additional Resources
Problems
Inferences About Proportions
What Inferences About Proportions Involving the Normal Distribution Are and How They Work
What Inferences About Proportions Involving the Chi-Square Distribution Are and How They Work
Computing Inferences About Proportions Involving the Chi-Square Distribution Using SPSS
Computing Inferences About Proportions Involving the Chi-Square Distribution Using R
Data Screening
Power Using G*Power
Recommendations
Research Question Template and Example Write-Up
Additional Resources
Problems
Inferences About Variances
Inferences About Variances and How They Work
Assumptions
Sample Size, Power, and Effect Size
Computing Inferences About Variances Using SPSS
Computing Inferences About Variances Using R
Research Question Template and Example Write-Up
Additional Resources
Problems
Bivariate Measures of Association
What Bivariate Measures of Association Are and How They Work
Computing Bivariate Measures of Association Using SPSS
Computing Bivariate Measures of Association Using R
Data Screening
Power Using G*Power
Research Question Template and Example Write-Up
Additional Resources
Problems
AppendixName Index
Subject Index