Statistics for the Life Sciences, Global Edition

Häftad, Engelska, 2015

AvMyra Samuels,Jeffrey Witmer,Andrew Schaffner

1 479 kr

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For introductory undergraduate or graduate courses in statistics aimed at life science majors.

The 5th Edition of Statistics for the Life Sciences uses authentic examples and exercises from a wide variety of life science domains to give statistical concepts personal relevance, enabling students to connect concepts with situations they will encounter outside the classroom. The emphasis on understanding ideas rather than memorising formulas makes the text ideal for students studying a variety of scientific fields: animal science, agronomy, biology, forestry, health, medicine, nutrition, pharmacy, physical education, zoology and more. In the 5th Edition, randomisation tests have been moved to the fore to motivate the inference procedures introduced in the text. There are no prerequisites for the text except elementary algebra.

Produktinformation

Utgivningsdatum2015-09-02
Mått216 x 275 x 39 mm
Vikt2 168 g
FormatHäftad
SpråkEngelska
Antal sidor656
Upplaga5
FörlagPearson Education
ISBN9781292101811

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Matematisk statistik inom Naturvetenskap och teknik

UNIT I: DATA AND DISTRIBUTIONS1. Introduction1.1 Statistics and the Life Sciences1.2 Types of Evidence1.3 Random Sampling 2. Description of Samples and Populations2.1 Introduction2.2 Frequency Distributions2.3 Descriptive Statistics: Measures of Center2.4 Boxplots2.5 Relationships Between Variables2.6 Measures of Dispersion2.7 Effect of Transformation of Variables 2.8 Statistical Inference2.9 Perspective 3. Probability and the Binomial Distribution3.1 Probability and the Life Sciences3.2 Introduction to Probability3.3 Probability Rules (Optional)3.4 Density Curves3.5 Random Variables3.6 The Binomial Distribution3.7 Fitting a Binomial Distribution to Data (Optional) 4. The Normal Distribution4.1 Introduction4.2 The Normal Curves4.3 Areas under a Normal Curve4.4 Assessing Normality4.5 Perspective 5. Sampling Distributions5.1 Basic Ideas5.2 The Sample Mean5.3 Illustration of the Central Limit Theorem5.4 The Normal Approximation to the Binomial Distribution5.5 Perspective Unit I Highlights and Study UNIT II: INFERENCE FOR MEANS 6. Confidence Intervals6.1 Statistical Estimation6.2 Standard Error of the Mean6.3 Confidence Interval for μ6.4 Planning a Study to Estimate μ6.5 Conditions for Validity of Estimation Methods6.6 Comparing Two Means6.7 Confidence Interval for (μ1 - μ2)6.8 Perspective and Summary 7. Comparison of Two Independent Samples7.1 Hypothesis Testing: The Randomization Test7.2 Hypothesis Testing: The t Test7.3 Further Discussion of the t Test7.4 Association and Causation7.5 One-Tailed t Tests7.6 More on Interpretation of Statistical Significance7.7 Planning for Adequate Power 7.8 Student’s t: Conditions and Summary7.9 More on Principles of Testing Hypotheses7.10 The Wilcoxon-Mann-Whitney Test 8. Comparison of Paired Samples8.1 Introduction8.2 The Paired-Sample t Test and Confidence Interval8.3 The Paired Design8.4 The Sign Test8.5 The Wilcoxon Signed-Rank Test8.6 Perspective Unit II Highlights and Study UNIT III: INFERENCE FOR CATEGORICAL DATA9. Categorical Data: One-Sample Distributions9.1 Dichotomous Observations9.2 Confidence Interval for a Population Proportion9.3 Other Confidence Levels (Optional)9.4 Inference for Proportions: The Chi-Square Goodness-of-Fit Test9.5 Perspective and Summary 10. Categorical Data: Relationships10.1 Introduction10.2 The Chi-Square Test for the 2 × 2 Contingency Table10.3 Independence and Association in the 2 × 2 Contingency Table10.4 Fisher’s Exact Test 10.5 The r × k Contingency Table10.6 Applicability of Methods10.7 Confidence Interval for Difference Between Probabilities10.8 Paired Data and 2 × 2 Tables 10.9 Relative Risk and the Odds Ratio 10.10 Summary of Chi-Square Test Unit III Highlights and Study UNIT IV: MODELING RELATIONSHIPS11. Comparing the Means of Many Independent Samples11.1 Introduction11.2 The Basic One-Way Analysis of Variance11.3 The Analysis of Variance Model11.4 The Global F Test11.5 Applicability of Methods11.