Table of Contents

What is statistics? Descriptive and inferential statistics.
Organizing and graphing data.
Descriptive methods: Measures of central tendency and variability.
Foundation of standard normal distribution: Describing individual scores.
Measuring relationships: Correlation.
Making predictions: Regression.
The standard normal distribution.
Hypothesis testing: One sample case for the mean.
Hypothesis testing: Two sample cases for the mean.
Making inferences about population proportions.
Estimating population parameters.
Analysis of variance: One-way.
Categorical analysis: Chi-square tests.
Not the most widely-used methods but important to know for determining "practical and personal significance".
Useful research designs for clinical studies: Fundamental concepts, foundations, and procedures.
Appendices. "This text will help readers comprehend how the process of clinical research relates to the scientific method of problem solving. Readers will understand the importance of three key, interrelated tasks involved in a research study: description (why it was done), explanation (what was done and to whom), and contextualization (how the results relate to other bodies of knowledge)." "This book not only distinguishes between the concepts of "statistical significance" and "clinical significance," often not clearly addressed in other texts, but it also emphasizes the value of scientific literacy in evidence-based practice."--Provided by publisher.