Description
The dynamic, student focused textbook provides step-by-step instruction in the use of R and of statistical language as a general research tool. It is ideal for anyone hoping to:
Complete an introductory course in statistics
Prepare for more advanced statistical courses
Gain the transferable analytical skills needed to interpret research from across the social sciences
Learn the technical skills needed to present data visually
Acquire a basic competence in the use of R.
The book provides readers with the conceptual foundation to use applied statistical methods in everyday research. Each statistical method is developed within the context of practical, real-world examples and is supported by carefully developed pedagogy and jargon-free definitions. Theory is introduced as an accessible and adaptable tool and is always contextualized within the pragmatic context of real research projects and definable research questions.
Author Robert Stinerock has also created a wide range of online resources, including: R scripts, complete solutions for all exercises, data files for each chapter, video and screen casts, and interactive multiple-choice quizzes.
KEY FEATURES:
In-depth R tutorials that start from the act of locating and downloading the software and continue through each statistical method
Shows readers how to use R in a gradual way that builds confidence and eliminates fear
Grounds each statistical method in practical, real world examples that are both timely and interdisciplinary
Provides carefully cultivated, jargon-free pedagogy that appeals to different learning styles through a mix of text, visuals, and off the page learning
Provides readers with a step-by-step guide to statistical language that includes a variety of resources for reflection, revision, and practice
Table of Contents
Chapter 1: Introduction and R Instructions
Chapter 2: Descriptive Statistics: Tabular and Graphical Methods
Chapter 3: Descriptive Statistics: Numerical Methods
Chapter 4: Introduction to Probability
Chapter 5: Discrete Probability Distributions
Chapter 6: Continuous Probability Distributions
Chapter 7: Point Estimation and Sampling Distributions
Chapter 8: Confidence Interval Estimation
Chapter 9: Hypothesis Tests: Introduction, Basic Concepts, and an Example
Chapter 10: Hypothesis Tests About u and p: Applications
Chapter 11: Comparisons of Means and Proportions
Chapter 12: Simple Linear Regression
Chapter 13: Multiple Regression
Robert Stinerock - Universidade Nova de Lisboa, Portugal