The Analysis of Biological Data Solutions Manual 1st Edition by Michael C Whitlock, Dolph Schluter ISBN 0981519407 9780981519401

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ISBN 10: 0981519407 
ISBN 13: 9780981519401
Author: Michael C Whitlock, Dolph Schluter

Now available with Macmillan’s new online learning platform Achieve, Analysis of Biological Data is beloved by instructors and students for providing a practical foundation of statistics for biology students. Every chapter has several biological or medical examples related to key statistics concepts, and each example is prefaced by a substantial description of the biological setting. The emphasis on real and interesting examples carries into the problem sets where students have a wealth of practice problems based on real data.

The third edition features over 200 new examples and problems. These include new calculation practice problems, which guide the student step by step through the methods, and a greater number of examples and topics that come from medical and human health research.  Every chapter has been carefully edited for even greater clarity and ease of use, and is easier than ever to access through Achieve.

Achieve for Analysis of Biological Data connects the problem-solving approach and real world examples in the book to rich digital resources that foster further understanding and application of statistics. Assets in Achieve support learning before, during, and after class for students, while providing instructors with class performance analytics in an easy-to-use interface.

The Analysis of Biological Data Solutions Manual 1st Table of contents:

Chapter 1: Introduction to Biological Data and Statistics

1.1 Overview of Biological Data
1.2 Types of Data in Biology
1.3 Descriptive Statistics and Summarizing Data
– Solution 1.1: Summary of Data Using Measures of Central Tendency
– Solution 1.2: Variance and Standard Deviation Calculations
– Solution 1.3: Histogram Analysis
1.4 Graphical Methods in Data Presentation
– Solution 1.4: Creating Box Plots
– Solution 1.5: Scatter Plot Interpretation

Chapter 2: Probability and Probability Distributions

2.1 Introduction to Probability
2.2 Discrete Probability Distributions
– Solution 2.1: Binomial Distribution Analysis
2.3 Continuous Probability Distributions
– Solution 2.2: Normal Distribution and Standardization
– Solution 2.3: Applying the Poisson Distribution in Biology
2.4 The Central Limit Theorem
– Solution 2.4: Using the Central Limit Theorem in Biological Context

Chapter 3: Hypothesis Testing

3.1 Introduction to Hypothesis Testing
3.2 The Null and Alternative Hypotheses
3.3 Type I and Type II Errors
– Solution 3.1: Error Analysis in Hypothesis Testing
3.4 t-tests and z-tests
– Solution 3.2: One-Sample t-test for Means
– Solution 3.3: Paired t-test for Differences Between Groups
– Solution 3.4: Two-Sample z-test for Proportions
3.5 p-Values and Statistical Significance
– Solution 3.5: Interpreting p-Values in Biological Research

Chapter 4: ANOVA and Experimental Design

4.1 Introduction to Analysis of Variance
4.2 One-Way ANOVA
– Solution 4.1: ANOVA Calculation and Interpretation
4.3 Two-Way ANOVA
– Solution 4.2: Interaction Effects in Two-Way ANOVA
4.4 Experimental Design Considerations
– Solution 4.3: Randomized Block Design Example

Chapter 5: Correlation and Regression Analysis

5.1 Understanding Correlation
– Solution 5.1: Pearson’s Correlation Coefficient
5.2 Simple Linear Regression
– Solution 5.2: Fitting a Regression Line and Interpretation
5.3 Multiple Linear Regression
– Solution 5.3: Model Fitting with Multiple Predictors
5.4 Logistic Regression
– Solution 5.4: Logistic Regression in Biological Studies

Chapter 6: Non-Parametric Methods

6.1 Introduction to Non-Parametric Tests
6.2 The Mann-Whitney U Test
– Solution 6.1: Mann-Whitney U Test for Two Independent Samples
6.3 The Kruskal-Wallis Test
– Solution 6.2: Kruskal-Wallis Test for Multiple Groups
6.4 The Wilcoxon Signed-Rank Test
– Solution 6.3: Wilcoxon Test for Paired Data

Chapter 7: Multivariate Analysis

7.1 Introduction to Multivariate Techniques
7.2 Principal Component Analysis (PCA)
– Solution 7.1: PCA Application to Ecological Data
7.3 Cluster Analysis
– Solution 7.2: Hierarchical Clustering Example
7.4 Discriminant Analysis
– Solution 7.3: Linear Discriminant Analysis for Classification

Chapter 8: Survival Analysis

8.1 Introduction to Survival Analysis
8.2 Kaplan-Meier Estimator
– Solution 8.1: Estimating Survival Curves
8.3 Cox Proportional Hazards Model
– Solution 8.2: Applying the Cox Model to Biological Data

Chapter 9: Bioinformatics and High-Throughput Data

9.1 Overview of Bioinformatics Methods
9.2 Analyzing Gene Expression Data
– Solution 9.1: Normalization and Differential Expression Analysis
9.3 Sequence Alignment and Statistical Methods
– Solution 9.2: Using BLAST for Sequence Comparison
9.4 Systems Biology Approaches
– Solution 9.3: Network Analysis of Biological Systems

Chapter 10: Special Topics in Biological Data Analysis

10.1 Bayesian Methods in Biological Research
– Solution 10.1: Bayesian Inference for Parameter Estimation
10.2 Analysis of Ecological and Evolutionary Data
– Solution 10.2: Modeling Population Dynamics with Biological Data
10.3 Advances in Statistical Software for Biology
– Solution 10.3: R and Python in Biological Data Analysis

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Tags: Michael C Whitlock, Dolph Schluter, Analysis, Biological Data