# Statistics for Health, Life and Social Sciences

por Denis Anthony
:
( 33 )
292 pages
Idioma:
English
There are many books concerned with statistical theory. This is not one of them.
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There are many books concerned with statistical theory. This is not one of them. 'Statistics for Health, Life and Social Sciences' is a practical book. It is aimed at people who need to understand statistics, but not develop it as a subject. The typical reader might be a postgraduate student in health, life or social science who has no knowledge of statistics, but needs to use quantitative methods in their studies. Students who are engaged in qualitative studies will need to read and understand quantitative studies when they do their literature reviews, this book may be of use to them.

This text is based on lectures given to students of nursing, midwifery, social work, probation, criminology, allied health, podiatry at undergraduate to doctoral level. However the examples employed, all from health, life and social sciences, should be understandable to any reader.

There is virtually no theory in this text, almost no mathematics (a bit of simple arithmetic is about as far as it gets). I do not give every statistical test, nor do I examine every restriction of any test. There are texts, good ones, that do all of these things. For example Field’s (Field, 2009)text is excellent and gives a fuller treatment, but his book is 820 pages long!

All books contain errors, or explanations that are not clear. If you note any email me on danthony@dmu.ac.uk and I will fix them. FIELD, A. 2009. Discovering statistics using SPSS (and sex and drugs and rock 'n' roll), London, Sage.

1. Designing questionnaires and surveys
1. Getting started in SPSS - Data entry
2. Introducing descriptive statistics
3. Graphs
4. Manipulating data
5. Chi square
6. Differences between two groups
7. Differences between more than two groups
8. Correlation
9. Paired tests
10. Measures of prediction: sensitivity, specificity and predictive values
12. Reliability
13. Internal reliability
14. Factor analysis
15. linear Regression
16. logistic regression
17. Cluster analysis
18. Introduction to power analysis
19. Which statistical tests to use
2. Endnotes