Description 
1 online resource (177 pages) 
Contents 
Cover  Title Page  Contents  Preface  Foreword to Students  1 INTRODUCTION  1.1 What do we mean by statistics?  1.2 Why is statistics necessary?  1.3 The limitations of statistics  1.4 Calculators and computers in statistics  1.5 The purpose of this teXt  2 HEALTH CARE INVESTIGATIONS: MEASUREMENT AND SAMPLING CONCEPTS  2.1 Introduction  2.2 Populations  2.3 Counting things  the sampling unit  2.4 Sampling strategy  2.5 Target and study populations  2.6 Sample designs  2.7 Simple random sampling  2.8 Systematic sampling  2.9 Stratified sampling  2.10 Quota sampling  2.11 Cluster sampling  2.12 Sampling designs  summary  2.13 Statistics and parameters  2.14 Descriptive and inferential statistics  2.15 Parametric and nonparametric statistics  3 PROCESSING DATA  3.1 Scales of measurement  3.2 The nominal scale  3.3 The ordinal scale  3.4 The interval scale  3.5 The ratio scale  3.6 Conversion of interval observations to an ordinal scale  3.7 Derived variables  3.8 Logarithms  3.9 The precision of observations  3.10 How precise should we be?  3.11 The frequency table  3.12 Aggregating frequency classes  3.13 Frequency distribution of count observations  3.14 Bivariate data  4 PRESENTING DATA  4.1 Introduction  4.2 Dot plot or line plot  4.3 Bar graph  4.4 Histogram  4.5 Frequency polygon and frequency curve  4.6 Scattergram  4.7 Circle or pie graph  5 CLINICAL TRIALS  5.1 Introduction  5.2 The nature of clinical trials  5.3 Clinical trial designs  5.4 Psychological effects and blind trials  5.5 Historical controls  5.6 Ethical issues  5.7 Case study: Leicestershire Electroconvulsive Therapy (ECT) study  5.8 Summary  6 INTRODUCTION TO EPIDEMIOLOGY  6.1 Introduction  6.2 Measuring disease 

11.3 The statistical hypothesis  11.4 Test statistics  11.5 Onetailed and twotailed tests  11.6 Hypothesis testing and the normal curve  11.7 Type 1 and type 2 errors  11.8 Parametric and nonparametric statistics: some further observations  11.9 The power of a test  12 ANALYSING FREQUENCIES  12.1 The chisquared test  12.2 Calculating the test statistic  12.3 A practical eXample of a test for homogeneous frequencies  12.4 One degree of freedom  Yates correction  12.5 Goodness of fit tests  12.6 The contingency table  tests for association  12.7 The 'rows by columns (r x c) contingency table  12.8 Larger contingency tables  12.9 Advice on analysing frequencies  13 MEASURING CORRELATIONS  13.1 The meaning of correlation  13.2 Investigating correlation  13.3 The strength and significance of a correlation  13.4 The Product Moment Correlation Coefficient  13.5 The coefficient of determination r2  13.6 The Spearman Rank Correlation Coefficient rs  13.7 Advice on measuring correlations  14 REGRESSION ANALYSIS  14.1 Introduction  14.2 Gradients and triangles  14.3 Dependent and independent variables  14.4 A perfect rectilinear relationship  14.5 The line of least squares  14.6 Simple linear regression  14.7 Fitting the regression line to the scattergram  14.8 Regression for estimation  14.9 The coefficient of determination in regression  14.10 Dealing with curved relationships  14.11 How we can 'straighten up curved relationships?  14.12 Advice on using regression analysis  15 COMPARING AVERAGES  15.1 Introduction  15.2 Matched and unmatched observations  15.3 The MannWhitney Utest for unmatched samples  15.4 Advice on using the MannWhitney Utest  15.5 More than two samples  the KruskalWallace test 

15.6 Advice on using the KruskalWallace test  15.7 The WilcoXon test for matched pairs  15.8 Advice on using the WilcoXon test for matched pairs  15.9 Comparing means  parametric tests  15.10 The ztest for comparing the means of two large samples  15.11 The ttest for comparing the means of two small samples  15.12 The ttest for matched pairs  15.13 Advice on comparing means  16 ANALYSIS OF VARIANCE  ANOVA  16.1 Why do we need ANOVA?  16.2 How ANOVA works  16.3 Procedure for computing ANOVA  16.4 The Tukey test  16.5 Further applications of ANOVA  16.6 Advice on using ANOVA  APPENDICES  AppendiX 1: Table of random numbers  AppendiX 2: tdistribution  AppendiX 3: (S{ (B2 distribution  AppendiX 4: Critical values of Spearman s Rank Correlation Coefficient  AppendiX 5: Critical values of the product moment correlation coefficient  AppendiX 6: MannWhitney Utest values (twotailed test)  AppendiX 7: Critical values of T in the WilcoXon test for matched pairs  AppendiX 8: Fdistribution  AppendiX 9: Tukey test  AppendiX 10: Symbols  AppendiX 11: Leicestershire ECT study data  AppendiX 12: How large should our samples be?  Bibliography  Index 

6.3 Study designs  cohort studies  6.4 Study designs  casecontrol studies  6.5 Cohort or casecontrol study?  6.6 Choice of comparison group  6.7 Confounding  6.8 Summary  7 MEASURING THE AVERAGE  7.1 What is an average?  7.2 The mean  7.3 Calculating the mean of grouped data  7.4 The median  a resistant statistic  7.5 The median of a frequency distribution  7.6 The mode  7.7 Relationship between mean, median and mode  8 MEASURING VARIABILITY  8.1 Variability  8.2 The range  8.3 The standard deviation  8.4 Calculating the standard deviation  8.5 Calculating the standard deviation from grouped data  8.6 Variance  8.7 An alternative formula for calculating the variance and standard deviation  8.8 Obtaining the standard deviation and sum of squares from a calculator  8.9 Degrees of freedom  8.10 The Coefficient of Variation (CV)  9 PROBABILITY AND THE NORMAL CURVE  9.1The meaning of probability  9.2 Compound probabilities  9.3 Critical probability  9.4 Probability distribution  9.5 The normal curve  9.6 Some properties of the normal curve  9.7 Standardizing the normal curve  9.8 Twotailed or onetailed?  9.9 Small samples: the tdistribution  9.10 Are our data 'normal ?  9.11 Dealing with 'nonnormal data  10 HOW GOOD ARE OUR ESTIMATES?95  10.1 Sampling error  10.2 The distribution of a sample mean  10.3 The confidence interval of a mean of a large sample  10.4 The confidence interval of a mean of a small sample  10.5 The difference between the means of two large samples  10.6 The difference between the means of two small samples  10.7 Estimating a proportion  10.8 The finite population correction  11 THE BASIS OF STATISTICAL TESTING  11.1 Introduction  11.2 The eXperimental hypothesis 
Summary 
A knowledge of statistics is becoming increasingly necessary for nurses and other health care professionals if they are to read research reports, critically appraise the empirical literature and utilise research in their practice. Practical Statistics for Nursing and Health Care gently introduces the essential statistical techniques in an accessible manner to enable the reader to grasp the fundamentals and gain the confidence and understanding to perform their own analysis. Starting from first principles, the text then progresses step by step, with 'advice' sections for all the tests described. Including comprehensive coverage of all basic statistical concepts, information is also provided on relevant examples for nurses, including case studies, data sets and guidance for further reading. Advice is also given in areas such as clinical trials and epidemiology equipping the reader to critically appraise work published in key medical journals. Practical Statistics for Nursing and Healthcare: Provides a userfriendly guide to statistical techniques and applications relevant to nurses and health careworkers. Includes a variety of the most appropriate methods for gathering, presenting and analysing data. Features essential tables of data, illustrations and numerous fullyworked examples. An essential introduction to statistics for preregistration nursing students on diploma and degree courses and a revision aid for practising nurses and healthcare professionals 
Notes 
Description based on publisher supplied metadata and other sources 
Subject 
Medical statistics.


Medicine.


Nursing  Research  Statistical methods.

Form 
Electronic book

Author 
Chevannes, Mel.


Jarvis, Phil (Statistician)

ISBN 
111868561X 

9781118685617 
