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Nursing is a growing area of higher education, in which anintroduction to statistics is an essential component. There iscurrently a gap in the market for a 'user-friendly' book which iscontextulised and targeted for nursing. Practical Statistics forNursing and Health Care introduces statistical techniques in such away that readers will easily grasp the fundamentals to enable themto gain the confidence and understanding to perform their ownanalysis. It also provides sufficient advice in areas such asclinical trials and epidemiology to enable the reader to criticallyappraise work published in…mehr
Nursing is a growing area of higher education, in which anintroduction to statistics is an essential component. There iscurrently a gap in the market for a 'user-friendly' book which iscontextulised and targeted for nursing. Practical Statistics forNursing and Health Care introduces statistical techniques in such away that readers will easily grasp the fundamentals to enable themto gain the confidence and understanding to perform their ownanalysis. It also provides sufficient advice in areas such asclinical trials and epidemiology to enable the reader to criticallyappraise work published in journals such as the Lancet and BritishMedical Journal. * Covers all basic statistical concepts and tests * Is user-friendly - avoids excessive jargon * Includes relevant examples for nurses, including case studies anddata sets * Provides information on further reading * Starts from first principles and progresses step by step * Includes 'advice on' sections for all of the tests described
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Jim Fowler is a lecturer with the Department of Biological Sciences at De Montfort University in Scraptoft, Leicester, UK. Phil Jarvis is a consultant statistician for Astra Zeneca Pharmaceuticals in the UK.
PREFACE xiFOREWORD TO STUDENTS xv1 INTRODUCTION 11.1 What do we mean by statistics? 11.2 Why is statistics necessary? 11.3 The limitations of statistics 21.4 Performing statistical calculations 21.5 The purpose of this text 32 HEALTH CARE INVESTIGATIONS: MEASUREMENT AND SAMPLING CONCEPTS 52.1 Introduction 52.2 Populations, samples and observations 52.3 Counting things - the sampling unit 62.4 Sampling strategy 72.5 Target and study populations 82.6 Sample designs 82.7 Simple random sampling 92.8 Systematic sampling 92.9 Stratified sampling 102.10 Quota sampling 112.11 Cluster sampling 122.12 Sampling designs - summary 122.13 Statistics and parameters 132.14 Descriptive and inferential statistics 132.15 Parametric and non-parametric statistics 143 PROCESSING DATA 153.1 Scales of measurement 153.2 The nominal scale 153.3 The ordinal scale 163.4 The interval scale 173.5 The ratio scale 173.6 Conversion of interval observations to an ordinal scale 173.7 Derived variables 193.8 Logarithms 203.9 The precision of observations 213.10 How precise should we be? 223.11 The frequency table 223.12 Aggregating frequency classes 243.13 Frequency distribution of count observations 263.14 Bivariate data 274 PRESENTING DATA 294.1 Introduction 294.2 Dot plot or line plot 294.3 Bar graph 304.4 Histogram 324.5 Frequency polygon and frequency curve 334.5 Centiles and growth charts 354.7 Scattergram 354.8 Circle or pie graph 355 CLINICAL TRIALS 395.1 Introduction 395.2 The nature of clinical trials 395.3 Clinical trial designs 405.4 Psychological effects and blind trials 415.5 Historical controls 425.6 Ethical issues 435.7 Case study: Leicestershire Electroconvulsive Therapy (ECT) study 435.8 Summary 456 INTRODUCTION TO EPIDEMIOLOGY 476.1 Introduction 476.2 Measuring disease 486.3 Study designs - cohort studies 506.4 Study designs - case-control studies 516.5 Cohort or case-control study? 536.6 Choice of comparison group 546.7 Confounding 556.8 Summary 567 MEASURING THE AVERAGE 577.1 What is an average? 577.2 The mean 577.3 Calculating the mean of grouped data 597.4 The median - a resistant statistic 607.5 The median of a frequency distribution 617.6 The mode 627.7 Relationship between mean, median and mode 648 MEASURING VARIABILITY 658.1 Variability 658.2 The range 658.3 The standard deviation 668.4 Calculating the standard deviation 678.5 Calculating the standard deviation from grouped data 688.6 Variance 698.7 An alternative formula for calculating the variance and standard deviation 708.8 Degrees of freedom 718.9 The Coefficient of Variation (CV) 729 PROBABILITY AND THE NORMAL CURVE 759.1 The meaning of probability 759.2 Compound probabilities 769.3 Critical probability 789.4 Probability distribution 799.5 The normal curve 819.6 Some properties of the normal curve 829.7 Standardizing the normal curve 839.8 Two-tailed or one-tailed? 849.9 Small samples: the t-distribution 869.10 Are our data normally distributed? 889.11 Dealing with 'non-normal' data 9110 HOW GOOD ARE OUR ESTIMATES? 9510.1 Sampling error 9510.2 The distribution of a sample mean 9510.3 The confidence interval of a mean of a large sample 9810.4 The confidence interval of a mean of a small sample 9910.5 The difference between the means of two large samples 10010.6 The difference between the means of two small samples 10210.7 Estimating a proportion 10310.8 The finite population correction 10511 THE BASIS OF STATISTICAL TESTING 10711.1 Introduction 10711.2 The experimental hypothesis 10711.3 The statistical hypothesis 10811.4 Test statistics 11011.5 One-tailed and two-tailed tests 11011.6 Hypothesis testing and the normal curve 11111.7 Type 1 and type 2 errors 11311.8 Parametric and non-parametric statistics: some further observations 11311.9 The power of a test 11412 ANALYSING FREQUENCIES 11512.1 The chi-squared test 11512.2 Calculating the test statistic 11512.3 A practical example of a test for homogeneous frequencies 11812.4 One degree of freedom - Yates' correction 11912.5 Goodness of fit tests 12012.6 The contingency table - tests for association 12112.7 The 'rows by columns' (r × c) contingency table 12512.8 Larger contingency tables 12712.9 Advice on analysing frequencies 12913 MEASURING CORRELATIONS 13113.1 The meaning of correlation 13113.2 Investigating correlation 13113.3 The strength and significance of a correlation 13313.4 The Product Moment Correlation Coefficient 13413.5 The coefficient of determination r2 13613.6 The Spearman Rank Correlation Coefficient rs 13713.7 Advice on measuring correlations 13914 REGRESSION ANALYSIS 14114.1 Introduction 14114.2 Gradients and triangles 14214.3 Dependent and independent variables 14314.4 A perfect rectilinear relationship 14414.5 The line of least squares 14614.6 Simple linear regression 14714.7 Fitting the regression line to the scattergram 15014.8 Regression for estimation 15014.9 The coefficient of determination in regression 15114.10 Dealing with curved relationships 15214.11 How we can 'straighten up' curved relationships? 15514.12 Advice on using regression analysis 15515 COMPARING AVERAGES 15715.1 Introduction 15715.2 Matched and unmatched observations 15815.3 The Mann-Whitney U-test for unmatched samples 15815.4 Advice on using the Mann-Whitney U-test 16015.5 More than two samples - the Kruskal-Wallace test 16115.6 Advice on using the Kruskal-Wallace test 16315.7 The Wilcoxon test for matched pairs 16415.8 Advice on using the Wilcoxon test for matched pairs 16715.9 Comparing means - parametric tests 16815.10 The z-test for comparing the means of two large samples 16815.11 The t-test for comparing the means of two small samples 17015.12 The t-test for matched pairs 17115.13 Advice on comparing means 17316 ANALYSIS OF VARIANCE -ANOVA 17516.1 Why do we need ANOVA? 17516.2 How ANOVA works 17616.3 Procedure for computing ANOVA 17816.4 The Tukey test 18116.5 Further applications of ANOVA 18316.6 Advice on using ANOVA 185APPENDICES 187Appendix 1: Table of random numbers 187Appendix 2: t-distribution 188Appendix 3: chi2-distribution 189Appendix 4: Critical values of Spearman's Rank Correlation Coefficient 190Appendix 5: Critical values of the product moment correlation coefficient 191Appendix 6: Mann-Whitney U-test values (two-tailed test) 192Appendix 7: Critical values of T in the Wilcoxon test for matched pairs 193Appendix 8: F-distribution 194Appendix 9: Tukey test 198Appendix 10: Symbols 200Appendix 11: Leicestershire ECT study data 201Appendix 12: How large should our samples be? 203BIBLIOGRAPHY 209INDEX 211
"The language is friendly and puts the reader at ease ....This book provides comprehensive coverage of an area that is important to all health care professionals. (Nursing Times, 28 March 2002)"...a plain English guide...to facilitate both learning and reference..." (Nurse Education Today, No.23,2003)"...helpful in enabling nurses to appraise empirical research and utilise research in their practice..." (Primary Health Care, October 2003)"...provides clear explanations of the statistical concepts and illustrates these using relevant nursing scenarios..." (Practice Nurse, Friday 16 January, 2004)"...provides a basic foundation of statistics...good resource for nurses...very user friendly..." (Oncology Nursing Forum, Vol31(2), 2004)
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