LEADER 06987nam 22011893u 450 001 9910954714203321 005 20240405034811.0 010 $a9781118920558 010 $a1118920554 035 $a(CKB)3860000000012444 035 $a(EBL)1779316 035 $a(OCoLC)890146503 035 $a(SSID)ssj0001333834 035 $a(PQKBManifestationID)12603710 035 $a(PQKBTitleCode)TC0001333834 035 $a(PQKBWorkID)11392192 035 $a(PQKB)11339036 035 $a(MiAaPQ)EBC1779316 035 $a(MiAaPQ)EBC7104232 035 $a(Au-PeEL)EBL7104232 035 $a(Perlego)1000919 035 $a(EXLCZ)993860000000012444 100 $a20161017d2014|||| u|| | 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStarting out in Statistics $eAn Introduction for Students of Human Health, Disease, and Psychology 205 $a1st ed. 210 $aSomerset $cWiley$d2014 215 $a1 online resource (312 p.) 225 1 $aNew York Academy of Sciences 300 $aDescription based upon print version of record. 311 08$a9781118384022 311 08$a1118384024 327 $aStarting Out in Statistics; Contents; Introduction - What's the Point of Statistics?; Reference; Basic Maths for Stats Revision; Statistical Software Packages; About the Companion Website; 1 Introducing Variables, Populations and Samples - 'Variability is the Law of Life'; 1.1 Aims; 1.2 Biological data vary; 1.3 Variables; 1.4 Types of qualitative variables; 1.4.1 Nominal variables; 1.4.2 Multiple response variables; 1.4.3 Preference variables; 1.5 Types of quantitative variables; 1.5.1 Discrete variables; 1.5.2 Continuous variables; 1.5.3 Ordinal variables - a moot point 327 $a1.6 Samples and populations1.7 Summary; Reference; 2 Study Design and Sampling - 'Design is Everything. Everything!'; 2.1 Aims; 2.2 Introduction; 2.3 One sample; 2.4 Related samples; 2.5 Independent samples; 2.6 Factorial designs; 2.7 Observational study designs; 2.7.1 Cross-sectional design; 2.7.2 Case-control design; 2.7.3 Longitudinal studies; 2.7.4 Surveys; 2.8 Sampling; 2.9 Reliability and validity; 2.10 Summary; References; 3 Probability - 'Probability ... So True in General'; 3.1 Aims; 3.2 What is probability?; 3.3 Frequentist probability; 3.4 Bayesian probability 327 $a3.5 The likelihood approach3.6 Summary; References; 4 Summarising Data - 'Transforming Data into Information'; 4.1 Aims; 4.2 Why summarise?; 4.3 Summarising data numerically - descriptive statistics; 4.3.1 Measures of central location; 4.3.2 Measures of dispersion; 4.4 Summarising data graphically; 4.5 Graphs for summarising group data; 4.5.1 The bar graph; 4.5.2 The error plot; 4.5.3 The box-and-whisker plot; 4.5.4 Comparison of graphs for group data; 4.5.5 A little discussion on error bars; 4.6 Graphs for displaying relationships between variables; 4.6.1 The scatter diagram or plot 327 $a4.6.2 The line graph4.7 Displaying complex (multidimensional) data; 4.8 Displaying proportions or percentages; 4.8.1 The pie chart; 4.8.2 Tabulation; 4.9 Summary; References; 5 Statistical Power - '. . . Find out the Cause of this Effect'; 5.1 Aims; 5.2 Power; 5.3 From doormats to aortic valves; 5.4 More on the normal distribution; 5.4.1 The central limit theorem; 5.5 How is power useful?; 5.5.1 Calculating the power; 5.5.2 Calculating the sample size; 5.6 The problem with p values; 5.7 Confidence intervals and power; 5.8 When to stop collecting data 327 $a5.9 Likelihood versus null hypothesis testing5.10 Summary; References; 6 Comparing Groups using t-Tests and ANOVA - 'To Compare is not to Prove'; 6.1 Aims; 6.2 Are men taller than women?; 6.3 The central limit theorem revisited; 6.4 Student's t-test; 6.4.1 Calculation of the pooled standard deviation; 6.4.2 Calculation of the t statistic; 6.4.3 Tables and tails; 6.5 Assumptions of the t-test; 6.6 Dependent t-test; 6.7 What type of data can be tested using t-tests?; 6.8 Data transformations; 6.9 Proof is not the answer; 6.10 The problem of multiple testing 327 $a6.11 Comparing multiple means - the principles of analysis of variance 330 $aTo form a strong grounding in human-related sciences it is essential for students to grasp the fundamental concepts of statistical analysis, rather than simply learning to use statistical software. Although the software is useful, it does not arm a student with the skills necessary to formulate the experimental design and analysis of a research project in later years of study or indeed, if working in research. This textbook deftly covers a topic that many students find difficult. With an engaging and accessible style it provides the necessary background and tools for students to use statist 410 0$aNew York Academy of Sciences 606 $aMedical statistics -- Textbooks 606 $aMedical statistics$vTextbooks 606 $aHealth Care Evaluation Mechanisms 606 $aMedicine 606 $aMethods 606 $aMathematics 606 $aResearch 606 $aEpidemiologic Methods 606 $aEnvironment and Public Health 606 $aHealth 606 $aInvestigative Techniques 606 $aNatural Science Disciplines 606 $aScience 606 $aPopulation Characteristics 606 $aQuality of Health Care 606 $aHealth Occupations 606 $aDelivery of Health Care 606 $aHealth Care Quality, Access, and Evaluation 606 $aPublic Health 606 $aStatistics as Topic 606 $aResearch Design 606 $aPublic Health$2HILCC 606 $aHealth & Biological Sciences$2HILCC 606 $aMedical Statistics$2HILCC 615 4$aMedical statistics -- Textbooks. 615 0$aMedical statistics 615 2$aHealth Care Evaluation Mechanisms. 615 2$aMedicine. 615 2$aMethods. 615 2$aMathematics. 615 2$aResearch. 615 2$aEpidemiologic Methods. 615 2$aEnvironment and Public Health. 615 2$aHealth. 615 2$aInvestigative Techniques. 615 2$aNatural Science Disciplines. 615 2$aScience. 615 2$aPopulation Characteristics. 615 2$aQuality of Health Care. 615 2$aHealth Occupations. 615 2$aDelivery of Health Care. 615 2$aHealth Care Quality, Access, and Evaluation. 615 2$aPublic Health. 615 2$aStatistics as Topic. 615 2$aResearch Design. 615 7$aPublic Health 615 7$aHealth & Biological Sciences 615 7$aMedical Statistics 676 $a610.2/1 700 $aDe Winter$b Patricia$f1968-$01807947 701 $aCahusac$b Peter$f1957-$01604492 801 0$bAU-PeEL 801 1$bAU-PeEL 801 2$bAU-PeEL 906 $aBOOK 912 $a9910954714203321 996 $aStarting out in Statistics$94357960 997 $aUNINA