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    Did you notice that the EBM website has been updated? If not, please have a look. Some careful research by the BMJ on what folk use and how they use it has led to a much more functional website. It may not look more beautiful, but navigating is much easier, more intuitive, and faster. For example, you can now search from the home page and get to the full search engine in 1 click. And the entire homepage provides always 1-click access to most of the important functions and links. Check the Online Tools: in addition to the emailed table of contents, there is now a citation tracker that allows you to track particular articles or issues. So please have a look—suggestions welcome.

    Of course the journal is not the only website that discusses evidence-based medicine. If you type evidence-based medicine into Google, you get a staggering 3 million+ entries. The number one entry is the Centre for Evidence-Based Medicine— From here you can download various EBM tools, including a full (and free) version of CATmaker and the CEBM workshops schedule.

    The core of the EBM journal is the abstracts: the valid and clinically relevant new research that we find from over 100 screened journals. However, we also aim to help readers with developments and ideas about the practice and teaching evidence-based medicine. One area of repeated requests is more about understanding statistics. So in this issue is the first of a new series of short and painless notes on statistics that we hope will be useful for both readers and teachers. The series aims to introduce the basic principles of statistics from the perspective of a reader rather than a doer of research. So we will focus on principles and meaning rather than formula and calculations. This first article provides an overview of measurement scales and their summary statistics. Subsequent notes will focus on measures of association (eg, relative risk and odds ratio), statistical inference using confidence intervals and p values, precision and bias (including sample size and power), the evaluation of diagnostic tests (predictive values), and survival analysis. Let us know if there is a statistical issue you would particularly like covered in the series.