Practice of Statistics in the Life Sciences, Digital Update, 4th Edition Brigitte Baldi, David Moore

Half I: Accumulating and Exploring Knowledge

Chapter 1 Picturing Distributions with Graphs

People and variables

Figuring out categorical and quantitative variables

Categorical variables: pie charts and bar graphs

Quantitative variables: histograms

Deciphering histograms

Quantitative variables: dotplots

Time plots

Dialogue: (Mis)adventures in knowledge entry

Chapter 2 Describing Quantitative Distributions with Numbers

Measures of heart: median, imply

Measures of unfold: percentiles, commonplace deviation

Graphical shows of numerical summaries

Recognizing suspected outliers*

Dialogue: Coping with outliers

Organizing a statistical downside

Chapter 3 Scatterplots and Correlation

Explanatory and response variables

Relationship between two quantitative variables: scatterplots

Including categorical variables to scatterplots

Measuring linear affiliation: correlation

Chapter 4 Regression

The least-squares regression line

Information about least-squares regression

Outliers and influential observations

Working with logarithm transformations*

Cautions about correlation and regression

Affiliation doesn’t indicate causation

Chapter 5 Two-Approach Tables

Marginal distributions

Conditional distributions

Simpson’s paradox

Chapter 6 Samples and Observational Research

Commentary versus experiment

Sampling

Sampling designs

Pattern surveys

Cohorts and case-control research

Chapter 7 Designing Experiments

Designing experiments

Randomized comparative experiments

Widespread experimental designs

Cautions about experimentation

Ethics in experimentation

Dialogue: The Tuskegee syphilis examine

Chapter 8 Accumulating and Exploring Knowledge: Half I Evaluation

Half I Abstract

Complete Evaluation Workout routines

Massive Dataset Workout routines

On-line Knowledge Sources

EESEE Case Research

Half II: From Likelihood to Inference

Chapter 9 Important Likelihood Guidelines

The thought of chance

Likelihood fashions

Likelihood guidelines

Discrete versus steady chance fashions

Random variables

Danger and odds*

Chapter 10 Independence and Conditional Chances*

Relationships amongst a number of occasions

Conditional chance

Common chance guidelines

Tree diagrams

Bayes’s theorem

Dialogue: Making sense of conditional chances in diagnostic checks

Chapter 11 The Regular Distributions

Regular distributions

The 68-95-99.7 rule

The usual Regular distribution

Discovering Regular chances

Discovering percentiles

Utilizing the commonplace Regular desk*

Regular quantile plots*

Chapter 12 Discrete Likelihood Distributions*

The binomial setting and binomial distributions

Binomial chances

Binomial imply and commonplace deviation

The Regular approximation to binomial distributions

The Poisson distributions

Poisson chances

Chapter 13 Sampling Distributions

Parameters and statistics

Statistical estimation and sampling distributions

The sampling distribution of the central restrict theorem

The sampling distribution of the legislation of massive numbers*

Chapter 14 Introduction to Inference

Statistical estimation

Margin of error and confidence stage

Confidence intervals for the imply

Speculation testing P-value and statistical significance

Exams for a inhabitants imply

Exams from confidence intervals

Chapter 15 Inference in Practice

Circumstances for inference in apply

How confidence intervals behave

How speculation checks behave

Dialogue: The scientific strategy

Planning research: choosing an applicable pattern dimension

Chapter 16 From Likelihood to Inference: Half II Evaluation

Half II Abstract

Complete Evaluation Workout routines

Superior Subjects (Optionally available Materials)

On-line Knowledge Sources

EESEE Case Research

Half III: Statistical Inference

Chapter 17 Inference a few Inhabitants Imply

Circumstances for inference

The t distributions

The one-sample t confidence interval

The one-sample t take a look at

Matched pairs t procedures

Robustness of t procedures

Chapter 18 Evaluating Two Means

Evaluating two inhabitants means

Two-sample t procedures

Robustness once more

Keep away from the pooled two-sample t procedures*

Keep away from inference about commonplace deviations*

Chapter 19 Inference a few Inhabitants Proportion

The pattern proportion

Massive-sample confidence intervals for a proportion

Correct confidence intervals for a proportion

Selecting the pattern dimension*

Speculation checks for a proportion

Chapter 20 Evaluating Two Proportions

Two-sample issues: proportions

The sampling distribution of a distinction between proportions

Massive-sample confidence intervals for evaluating proportions

Correct confidence intervals for evaluating proportions

Speculation checks for evaluating proportions

Relative threat and odds ratio*

Dialogue: Assessing and understanding well being dangers

Chapter 21 The Chi-Sq. Check for Goodness of Match

Hypotheses for goodness of match

The chi-square take a look at for goodness of match

Deciphering chi-square outcomes

Circumstances for the chi-square take a look at

The chi-square distributions

The chi-square take a look at and the one-sample z take a look at*

Chapter 22 The Chi-Sq. Check for Two-Approach Tables

Two-way tables

The issue of a number of comparisons

Anticipated counts in two-way tables

The chi-square take a look at

Circumstances for the chi-square take a look at

Makes use of of the chi-square take a look at

Utilizing a desk of crucial values*

The chi-square take a look at and the two-sample z take a look at*

Chapter 23 Inference for Regression

Circumstances for regression inference

Estimating the parameters

Testing the speculation of no linear relationship

Testing lack of correlation*

Confidence intervals for the regression slope

Inference about prediction

Checking the circumstances for inference

Chapter 24 One-Approach Evaluation of Variance: Evaluating A number of Means

Evaluating a number of means

The evaluation of variance F take a look at

The thought of evaluation of variance

Circumstances for ANOVA F-distributions and levels of freedom

The one-way ANOVA and the pooled two-sample t take a look at*

Particulars of ANOVA calculations*

Chapter 25 Statistical Inference: Half III Evaluation

Half III Abstract

Evaluation Workout routines

Supplementary Workout routines

EESEE Case Research

Half IV: Optionally available Companion Chapters

Chapter 26 Extra about Evaluation of Variance: Observe-up Exams and Two-Approach ANOVA

Past one-way ANOVA

Observe up evaluation: Tukey’s pairwise a number of comparisons

Observe up evaluation: contrasts*

Two-way ANOVA: circumstances, predominant results, and interplay

Inference for two-way ANOVA

Some particulars of two-way ANOVA*

Chapter 27 Nonparametric Exams

Evaluating two samples: the Wilcoxon rank sum take a look at

Matched pairs: the Wilcoxon signed rank take a look at

Evaluating a number of samples: the Kruskal-Wallis take a look at

Chapter 28 A number of and Logistic Regression

Parallel regression strains

Estimating parameters

Circumstances for inference

Inference for a number of regression

Interplay

A case examine for a number of regression

Logistic regression

Inference for logistic regression

Notes and Knowledge Sources

Tables

Solutions to Chosen Workout routines

Some Knowledge Units Recurring Throughout Chapters

Index