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.
Author(s): Debbie L. Hahs-Vaughn; Richard G. Lomax
Publisher: Routledge
Year: 2020
Language: English
Pages: xviii+442
Cover
Half Title
Title
Copyright
Dedication
Contents
Preface
Acknowledgments
1. Introduction
1.1 What Is the Value of Statistics?
1.2 Brief Introduction to the History of Statistics
1.3 General Statistical Definitions
1.4 Types of Variables
1.5 Scales of Measurement
1.6 Additional Resources
Problems
2. Data Representation
2.1 Tabular Display of Distributions
2.2 Graphical Display of Distributions
2.3 Percentiles
2.4 Recommendations Based on Measurement Scale
2.5 Computing Tables, Graphs, and More Using SPSS
2.6 Computing Tables, Graphs, and More Using R
2.7 Research Question Template and Example Write-Up
2.8 Additional Resources
Problems
3. Univariate Population Parameters and Sample Statistics
3.1 Summation Notation
3.2 Measures of Central Tendency
3.3 Measures of Dispersion
3.4 Computing Sample Statistics Using SPSS
3.5 Computing Sample Statistics Using R
3.6 Research Question Template and Example Write-Up
3.7 Additional Resources
Problems
4. The Normal Distribution and Standard Scores
4.1 The Normal Distribution and How It Works
4.2 Standard Scores and How They Work
4.3 Skewness and Kurtosis Statistics
4.4 Computing Graphs and Standard Scores Using SPSS
4.5 Computing Graphs and Standard Scores Using R
4.6 Research Question Template and Example Write-Up
4.7 Additional Resources
Problems
5. Introduction to Probability and Sample Statistics
5.1 Brief Introduction to Probability
5.2 Sampling and Estimation
5.3 Additional Resources
Problems
6. Introduction to Hypothesis Testing: Inferences About a Single Mean
6.1 Inferences About a Single Mean and How They Work
6.2 Computing Inferences About a Single Mean Using SPSS
6.3 Computing Inferences About a Single Mean Using R
6.4 Data Screening
6.5 Power Using G*Power
6.6 Research Question Template and Example Write-Up
6.7 Additional Resources
Problems
7. Inferences About the Difference Between Two Means
7.1 Inferences About Two Independent Means and How They Work
7.2 Inferences About Two Dependent Means and How They Work
7.3 Computing Inferences About Two Independent Means Using SPSS
7.4 Computing Inferences About Two Dependent Means Using SPSS
7.5 Computing Inferences About Two Independent Means Using R
7.6 Computing Inferences About Two Dependent Means Using R
7.7 Data Screening
7.8 G*Power
7.9 Research Question Template and Example Write-Up
7.10 Additional Resources
Problems
8. Inferences About Proportions
8.1 What Inferences About Proportions Involving the Normal Distribution Are and How They Work
8.2 What Inferences About Proportions Involving the Chi-Square Distribution Are and How They Work
8.3 Computing Inferences About Proportions Involving the Chi-Square Distribution Using SPSS
8.4 Computing Inferences About Proportions Involving the Chi-Square Distribution Using R
8.5 Data Screening
8.6 Power Using G*Power
8.7 Recommendations
8.8 Research Question Template and Example Write-Up
8.9 Additional Resources
Problems
9. Inferences About Variances
9.1 Inferences About Variances and How They Work
9.2 Assumptions
9.3 Sample Size, Power, and Effect Size
9.4 Computing Inferences About Variances Using SPSS
9.5 Computing Inferences About Variances Using R
9.6 Research Question Template and Example Write-Up
9.7 Additional Resources
Problems
10. Bivariate Measures of Association
10.1 What Bivariate Measures of Association Are and How They Work
10.2 Computing Bivariate Measures of Association Using SPSS
10.3 Computing Bivariate Measures of Association Using R
10.4 Data Screening
10.5 Power Using G*Power
10.6 Research Question Template and Example Write-Up
10.7 Additional Resources
Problems
Appendix
References
Name Index
Subject Index
