Medical Statistics Made Easy
By Michael Harris and Gordon Taylor
Jun 2014 , 128 pp
Jun 2014 , 128 pp
Medical Statistics Made Easy has been a perennial bestseller since it was first published in 2003 (#1 bestseller in medical statistics on Amazon). It is widely recommend on a variety of courses and programmes, from undergraduate medicine, through to professional medical qualifications.
It is a book of key statistics principles for anyone studying or working in medicine and healthcare who needs a basic overview of the subject.
Using a consistent format, the authors describe the most common statistical methods in turn and then rate them on how difficult they are to understand and how common they are.
The worked examples that demonstrate the statistical method in action have been updated to include current articles from the medical literature and now feature a much wider range of medical journals.
This third edition continues with the same structure as the previous editions and also features a completely revised "Statistics at work" section.
Medical Statistics Made Easy 3e scores 99/100 and 5 stars on Doody's (Sept 2014)! Here's what the reviewer said:
"This is a practical guide to the use of statistics in medical literature and their application in clinical practice. The numerous examples help make the conceptualization of complex ideas easy. It is a great resource for healthcare students and clinicians in the field."
Amazon 5-star reviews:
Fantastic book for someone who just needs to learn about the application and principles I love this book.
Helpful book, breaks statistics down into more manageable and less daunting chunks, includes information on how important each point is and how often it is used in real life The title doesn't lie.
For anyone that struggles with statistics, this is an absolute must.
Statistics which describe data:
Mean; Median; Mode; Standard deviation
Statistics which test confidence: Confidence intervals; P values
Statistics which test differences: t tests and other parametric tests; MannWhitney and other non-parametric tests; Chi-squared
Statistics which compare risk: Risk ratio; Odds ratio; Risk reduction and numbers needed to treat
Statistics which analyze relationships: Correlation; Regression
Statistics which analyze survival: Survival analysis: life tables and KaplanMeier plots; The Cox regression model
Statistics which analyze clinical investigations and screening: Sensitivity, specificity and predictive value; Level of agreement
Statistics at work: Medians, interquartile ranges and odds ratios; Risk ratios and number needed to treat; Correlation and regression; Survival analysis; Sensitivity, specificity and predictive values