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

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Check Financial institution For Practice of Statistics in the Life Sciences, Digital Replace, 4e Brigitte Baldi, David Moore

- ISBN-10 : 1319244424
- ISBN-13 : 978-1319244422

## Desk of Contents

**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

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