Statistical Methods in the Biological and Health Sciences
McGraw Hill Higher Education (Verlag)
978-0-07-290148-1 (ISBN)
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Milton's "Statistical Methods in the Biological and Health Sciences" offers comprehensive coverage for the applied statistics course, for health and bio-related majors. This course focuses primarily on developing basic statistical techniques and relevant applications within a framework that addresses the needs of these specific audiences.
1 Descriptive Methods1.1 Distribution Tables: Discrete DataBar GraphsBivariate Data: Two-Way Tables1.2 A Quick Look at Distribution: Stem and LeafConstructing a Simple Stem-and-Leaf Diagram1.3 Frequency Distributions: HistogramsRules for Breaking Data into ClassesCumulative Distribution1.4 Measures of Location or Central TendencySample MeanSample Median1.5 Measures of Variability or DispersionSample VarianceSample Standard DeviationSample RangeInterquartile RangeFinding the Sample Interquartile RangeMultiple Data Sets 1.6 Box Plots Constructing a Box Plot1.7 Handling Grouped Data 2 Introduction to Probability and Counting2.1 Interpreting Probablilities2.2 Tree Diagrams and Elementary GeneticsElementary Genetics 2.3 Permutations and Combinations 2.4 Multiplication Principle Guidelines for Using the Multiplication Principle2.5 Permutations of Indistinguishable Objects 2.6 Combinations 3 Probability and Problem Solving 3.1 Venn Diagrams and the Axioms of ProbabilityVenn DiagramsAxioms of Probability3.2 General Addition Rule3.3 Conditional Probability3.4 Diagnostic Tests and Relative RiskRelative Risk3.5 Independence3.6 The Multiplication Rule3.7 Bayes' Theorem4 Discrete Random Variables4.1 Discrete and Continuous Variables4.2 Discrete Density Functions and ExpectationExpectation4.3 Cumulative Distribution Function4.4 Binomial DistributionExpected Value and Variance: BinomialCalculating Binomial Probabilities: Cumulative Distribution4.5 Poisson Distribution 5 Continuous Random Variables5.1 Continuous Random VariablesExpectation5.2 Cumulative Distribution Function5.3 Normal DistributionProperties of Normal CurvesStandard Normal DistributionStandardization5.4 Normal Probability Rule and Medical Tables 6 Inferences on the Mean6.1 Random Sampling and Randomization Simple Random SamplingRandomization6.2 Point Estimation of the Mean and Introduction to Interval Estimation:Central Limit TheoremInterval EstimationCentral Limit Theorem6.3 Confidence Interval on the Population Mean and the T DistributionProperties of T Random Variables6.4 Introduction to Hypothesis Testing6.5 Testing Hypotheses on the PopulationMean: T TestPreset Alpha Values6.6 Sample Size: Confidence Intervals and Power Sample Size: Hypothesis Testing7 Chi-Squared Distribution and Inferences on the Variance7.1 Chi-Squared Distribution and Interval Estimation of the Population VarianceConfidence Interval on s2 7.2 Testing Hypotheses on the Population Variance 8 Inferences on Proportions8.1 Point Estimation8.2 Interval Estimation of p8.3 Sample Size for Estimating p8.4 Hypothesis Testing on p8.5 Comparing Two Proportions: EstimationConfidence Interval on the Difference in Two Proportions8.6 Comparing Two Proportions: Hypothesis TestingTesting That the Null Value Is Zero:Pooled Test9 Comparing Two Means and Two Variances9.1 Comparing Two Means and Two Variances9.2 Comparing Variances: F DistributionRule of Thumb Variance ComparisonF Test for Comparing Variances: F Distribution 9.3Inferences on m1 - m2: Pooled TInterval Estimation of m1 - m2Pooled T Tests9.4 Inferences on m1 - m2: Unequal Variances9.5 Inferences on m1 - m2: Paired TPaired T Test10 k-Sample Procedures: Introduction to Design10.1 One-Way Classification, Completely Random Design with Fixed EffectsData Format and Notation10.2 Paired and Multiple ComparisonsBonferroni T Tests: Paired ComparisonsDuncan's Multiple Range TestA Note on Computing10.3 Random Effects 10.4 Randomized Complete BlocksData Format and NotationTesting HO: m1. = m2. = @ @ @ = mk.Effectiveness of BlockingPaired and Multiple ComparisonsA Note on Computing10.5 Factorial ExperimentsData Format and NotationTesting Main Effects and InteractionMultiple and Paired ComparisonsA Note on Computing11 Regression and Correlation11.1 Introduction To Simple Linear Regression 11.2 Method of Least SquaresEstimating an Individual ResponseA Note on Computing11.3 Introduction to CorrelationEstimating r11.4 Evaluating the Strength of the Linear Relationship Coefficient of DeterminationAnalysis of VarianceA Note on Computing11.5 Confidence Interval Estimation 11.6 Multiple Regression 12 Categorical Data12.1 2 A' 2 Contingency TablesTest of IndependenceTest of Homogeneity12.2 r A' c Contingency Tables13 Some Additional Procedures and Distribution-Free Alternatives 13.1 Testing for Normality: The Lilliefors Test13.2 Tests of Location: One SampleSign Test for MedianWilcoxon Signed-Rank Test13.3 Tests of Location: Paired DataSign Test for Median DifferenceWilcoxon Signed-Rank Test: Paired Data13.4 Tests of Location: Unmatched DataWilcoxon Rank-Sum Test13.5 Kruskal-Wallis k-Sample Test forLocation: Unmatched DataKruskal-Wallis k-Sample Test13.6 Friedman k-Sample Test for Location: Matched DataFriedman Test13.7 CorrelationSpearman's Rank Correlation Coefficient13.8 Bartlett's Test for Equality of Variances13.9 Normal Approximations13.10 A Small Sample Test on ProportionsAppendix ASummation Notation and Rules for Expectation and VarianceSummation NotationRules for Expectation and VarianceAppendix BStatistical TablesReferencesAnswers to Odd-Numbered ProblemsIndex
| Erscheint lt. Verlag | 17.8.1998 |
|---|---|
| Zusatzinfo | tabs. |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 193 x 233 mm |
| Gewicht | 991 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Statistik |
| Studium ► Querschnittsbereiche ► Epidemiologie / Med. Biometrie | |
| Naturwissenschaften ► Biologie | |
| ISBN-10 | 0-07-290148-9 / 0072901489 |
| ISBN-13 | 978-0-07-290148-1 / 9780072901481 |
| Zustand | Neuware |
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