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Stats & Probability for Science & Medicine Textbooks

by Myra L. Samuels and Jeffrey A. Witmer

Edition: 2ND 99Copyright: 1999

Publisher: Prentice Hall, Inc.

Published: 1999

International: No

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**1. Introduction**

Statistics and the Life Sciences.

Examples and Overview.

**2. Description of Populations and Samples**

Introduction.

Frequency Distributions: Techniques for Data.

Frequency Distributions: Shapes and Examples.

Descriptive Statistics: Measures of Center.

Boxplots.

Measures of Dispersion.

Effect of Transformation of Variables (Optional).

Samples and Populations: Statistical Inference.

Perspective.

**3. Random Sampling, Probability, and the Binomial Distribution **

Probability and the Life Sciences.

Random Sampling.

Introduction to Probability.

Probability Trees.

Density Curves.

The Binomial Distribution.

Fitting a Binomial Distribution to Data (Optional).

**4. The Normal Distribution**

Introduction.

The Normal Curves.

Areas Under a Normal Curve.

Assessing Normality.

The Continuity Correction (Optional).

Perspective.

**5. Sampling Distributions**

Basic Ideas.

Dichotomous Observations.

Quantitative Observations.

Illustration of the Central Limit Theorem (Optional).

The Normal Approximation to the Binomial Distribution (Optional).

Perspective.

**6. Confidence Intervals **

Statistical Estimation.

Standard Error of the Mean.

Confidence Interval for u.

Planning a Study to Estimate u.

Conditions for Validity of Estimation Methods.

Confidence Interval for a Population Proportion.

Perspective and Summary.

**7. Comparison of Two Independent Samples**

Introduction.

Standard Error of (y1 - y2).

Confidence Interval for (u1 - u2).

Hypothesis Testing: The t-test.

Further Discussion of the t-test.

One-Tailed Tests.

More on Interpretation of Statistical Significance.

Planning for Adequate Power (Optional).

Student's t: Conditions and Summary.

More on Principles of Testing Hypotheses.

The Wilcoxon-Mann-Whitney Test.

Perspective.

**8. Statistical Principles of Design **

Introduction.

Observational Studies.

Experiments.

Restricted Randomization: Blocking and Stratification.

Levels of Replication.

Sampling Concerns (Optional).

Perspective.

**9. Comparison of Two Paired Samples **

Introduction.

The Paired-Sample t-Test and Confidence Interval.

The Paired Design.

The Sign Test.

Further Considerations in Paired Experiments.

Perspective.

**10. Analysis of Categorical Data **

Inference for Proportions: The Chi-Square Goodness-of-Fit Test.

The Chi-Square Test for the 2 X 2 Contingency Table.

Independence and Association in a 2 X 2 Contingency Table.

Fisher's Exact Test (Optional).

The r x k Contingency Table.

Applicability of Methods.

Confidence Interval for a Difference Between Proportions.

Paired Data and 2 X 2 Tables (Optional).

Relative Risks and the Odds Ratio (Optional).

Summary of Chi-Square Tests.

**11. Comparing the Means of k Independent Samples **

Introduction.

The Basic Analysis of Variance.

The Analysis of Variance Model (Optional).

The Global F Test.

Applicability of Methods.

Linear Combinations of Means (Optional).

Multiple Comparisons (Optional).

Perspective.

**12. Linear Regression and Correlation**

Introduction.

The Fitted Regression Line.

Parametric Interpretation of Regression: The Linear Model.

Statistical Inference Concerning B1.

Guidelines for Interpreting Regression and Correlation.

Perspective.

Summary of Formulas.

**13. A Summary of Inference Methods **

Introduction.

Data Analysis Samples.

Appendices.

Chapter Notes.

Statistical Tables.

Answers to Selected Exercises.

Index.

Index of Examples.

Table of Contents

**1. Introduction**

Statistics and the Life Sciences.

Examples and Overview.

**2. Description of Populations and Samples**

Introduction.

Frequency Distributions: Techniques for Data.

Frequency Distributions: Shapes and Examples.

Descriptive Statistics: Measures of Center.

Boxplots.

Measures of Dispersion.

Effect of Transformation of Variables (Optional).

Samples and Populations: Statistical Inference.

Perspective.

**3. Random Sampling, Probability, and the Binomial Distribution **

Probability and the Life Sciences.

Random Sampling.

Introduction to Probability.

Probability Trees.

Density Curves.

The Binomial Distribution.

Fitting a Binomial Distribution to Data (Optional).

**4. The Normal Distribution**

Introduction.

The Normal Curves.

Areas Under a Normal Curve.

Assessing Normality.

The Continuity Correction (Optional).

Perspective.

**5. Sampling Distributions**

Basic Ideas.

Dichotomous Observations.

Quantitative Observations.

Illustration of the Central Limit Theorem (Optional).

The Normal Approximation to the Binomial Distribution (Optional).

Perspective.

**6. Confidence Intervals **

Statistical Estimation.

Standard Error of the Mean.

Confidence Interval for u.

Planning a Study to Estimate u.

Conditions for Validity of Estimation Methods.

Confidence Interval for a Population Proportion.

Perspective and Summary.

**7. Comparison of Two Independent Samples**

Introduction.

Standard Error of (y1 - y2).

Confidence Interval for (u1 - u2).

Hypothesis Testing: The t-test.

Further Discussion of the t-test.

One-Tailed Tests.

More on Interpretation of Statistical Significance.

Planning for Adequate Power (Optional).

Student's t: Conditions and Summary.

More on Principles of Testing Hypotheses.

The Wilcoxon-Mann-Whitney Test.

Perspective.

**8. Statistical Principles of Design **

Introduction.

Observational Studies.

Experiments.

Restricted Randomization: Blocking and Stratification.

Levels of Replication.

Sampling Concerns (Optional).

Perspective.

**9. Comparison of Two Paired Samples **

Introduction.

The Paired-Sample t-Test and Confidence Interval.

The Paired Design.

The Sign Test.

Further Considerations in Paired Experiments.

Perspective.

**10. Analysis of Categorical Data **

Inference for Proportions: The Chi-Square Goodness-of-Fit Test.

The Chi-Square Test for the 2 X 2 Contingency Table.

Independence and Association in a 2 X 2 Contingency Table.

Fisher's Exact Test (Optional).

The r x k Contingency Table.

Applicability of Methods.

Confidence Interval for a Difference Between Proportions.

Paired Data and 2 X 2 Tables (Optional).

Relative Risks and the Odds Ratio (Optional).

Summary of Chi-Square Tests.

**11. Comparing the Means of k Independent Samples **

Introduction.

The Basic Analysis of Variance.

The Analysis of Variance Model (Optional).

The Global F Test.

Applicability of Methods.

Linear Combinations of Means (Optional).

Multiple Comparisons (Optional).

Perspective.

**12. Linear Regression and Correlation**

Introduction.

The Fitted Regression Line.

Parametric Interpretation of Regression: The Linear Model.

Statistical Inference Concerning B1.

Guidelines for Interpreting Regression and Correlation.

Perspective.

Summary of Formulas.

**13. A Summary of Inference Methods **

Introduction.

Data Analysis Samples.

Appendices.

Chapter Notes.

Statistical Tables.

Answers to Selected Exercises.

Index.

Index of Examples.

Publisher Info

Publisher: Prentice Hall, Inc.

Published: 1999

International: No

Published: 1999

International: No

**1. Introduction**

Statistics and the Life Sciences.

Examples and Overview.

**2. Description of Populations and Samples**

Introduction.

Frequency Distributions: Techniques for Data.

Frequency Distributions: Shapes and Examples.

Descriptive Statistics: Measures of Center.

Boxplots.

Measures of Dispersion.

Effect of Transformation of Variables (Optional).

Samples and Populations: Statistical Inference.

Perspective.

**3. Random Sampling, Probability, and the Binomial Distribution **

Probability and the Life Sciences.

Random Sampling.

Introduction to Probability.

Probability Trees.

Density Curves.

The Binomial Distribution.

Fitting a Binomial Distribution to Data (Optional).

**4. The Normal Distribution**

Introduction.

The Normal Curves.

Areas Under a Normal Curve.

Assessing Normality.

The Continuity Correction (Optional).

Perspective.

**5. Sampling Distributions**

Basic Ideas.

Dichotomous Observations.

Quantitative Observations.

Illustration of the Central Limit Theorem (Optional).

The Normal Approximation to the Binomial Distribution (Optional).

Perspective.

**6. Confidence Intervals **

Statistical Estimation.

Standard Error of the Mean.

Confidence Interval for u.

Planning a Study to Estimate u.

Conditions for Validity of Estimation Methods.

Confidence Interval for a Population Proportion.

Perspective and Summary.

**7. Comparison of Two Independent Samples**

Introduction.

Standard Error of (y1 - y2).

Confidence Interval for (u1 - u2).

Hypothesis Testing: The t-test.

Further Discussion of the t-test.

One-Tailed Tests.

More on Interpretation of Statistical Significance.

Planning for Adequate Power (Optional).

Student's t: Conditions and Summary.

More on Principles of Testing Hypotheses.

The Wilcoxon-Mann-Whitney Test.

Perspective.

**8. Statistical Principles of Design **

Introduction.

Observational Studies.

Experiments.

Restricted Randomization: Blocking and Stratification.

Levels of Replication.

Sampling Concerns (Optional).

Perspective.

**9. Comparison of Two Paired Samples **

Introduction.

The Paired-Sample t-Test and Confidence Interval.

The Paired Design.

The Sign Test.

Further Considerations in Paired Experiments.

Perspective.

**10. Analysis of Categorical Data **

Inference for Proportions: The Chi-Square Goodness-of-Fit Test.

The Chi-Square Test for the 2 X 2 Contingency Table.

Independence and Association in a 2 X 2 Contingency Table.

Fisher's Exact Test (Optional).

The r x k Contingency Table.

Applicability of Methods.

Confidence Interval for a Difference Between Proportions.

Paired Data and 2 X 2 Tables (Optional).

Relative Risks and the Odds Ratio (Optional).

Summary of Chi-Square Tests.

**11. Comparing the Means of k Independent Samples **

Introduction.

The Basic Analysis of Variance.

The Analysis of Variance Model (Optional).

The Global F Test.

Applicability of Methods.

Linear Combinations of Means (Optional).

Multiple Comparisons (Optional).

Perspective.

**12. Linear Regression and Correlation**

Introduction.

The Fitted Regression Line.

Parametric Interpretation of Regression: The Linear Model.

Statistical Inference Concerning B1.

Guidelines for Interpreting Regression and Correlation.

Perspective.

Summary of Formulas.

**13. A Summary of Inference Methods **

Introduction.

Data Analysis Samples.

Appendices.

Chapter Notes.

Statistical Tables.

Answers to Selected Exercises.

Index.

Index of Examples.