An introduction to statistics covers the concepts of measurement and probability theory, correlation, inferential techniques, and statistical analysis. Also he art of critiquing the statistics presented by others, inferential statistics, the t-test, the correlation coefficient, categorical data, nonparametric statistics, the general linear model, extensions of analysis of variance, multiple linear regression and other types of regression, and applications in business, quality improvement, medicine, epidemiology, education and psychology.
written for those who need to know how to collect, analyze and present data. It is meant to be a first course for practitioners, a book for private study or brush-up on statistics, and supplementary reading for general statistics classes
An introduction to statistical significance -- Statistical power and underpowered statistics -- Pseudoreplication : choose your data wisely -- The p value and the base rate fallacy -- Bad judges of significance -- Double-dipping in the data -- Continuity errors -- Model abuse -- Researcher freedom : good vibrations? -- Everybody makes mistakes -- Hiding the data -- What can be done?
Progresses through the basics, including analysis of variance and the t test, then advances to multiple comparison testing, contingency tables, regression, and more. Illustrative examples and challenging problems
Analyzes the way in which health and the conditions necessary for wellness are unequally distributed within society and argues that healthy societies foster healthy people.
Sociological foundations, the structural and behavioural factors that influence it, and the informal and formal components of the health-care system.
Introductory textbook explores the role of research in health care
Focuses in particular on the importance of organizing and describing research data using basic statistics
Teaches students how to analyze data and present the results of evidence-based data analysis
Useful course or in preparing for a medical board review. Topics as the study of risk and benefit in epidemiologic studies, statistical inference and hypothesis testing, principles and practice of secondary prevention, mental and behavioral health, and public health practice in communities.
ntroduction to statistics and levels of measurement -- Presenting data -- Descriptive statistics, probability, and measures of central tendency--Evaluating your measurement tool -- Sampling methods -- Generating the research idea -- Sample size, effect size, and power -- Chi-square -- Student t-test -- Analysis of variance (ANOVA) -- Correlation coefficients -- Regression analysis -- Relative risk, odds ratio, and attributable risk
essential information about statistical tests, concepts, and analytical methods in language that is accessible to practitioners and students of the vast community using statistics in medicine, engineering, physical science, life science, social science, and business/economics.