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9781446200469

Taschenbuch

01.04.2012

992

Andy Field

2250 g

264x192x50 mm

Englisch

The R version of Andy Field's hugely popular Discovering Statistics Using SPSS takes students on a journey of statistical discovery using the freeware R - a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences.

The R version of Andy Field's hugely popular Discovering Statistics Using SPSS takes students on a journey of statistical discovery using the freeware R - a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences.

Why Is My Evil Lecturer Forcing Me to Learn Statistics?

What will this chapter tell me?

What the hell am I doing here? I don't belong here

Initial observation: finding something that needs explaining

Generating theories and testing them

Data collection 1: what to measure

Data collection 2: how to measure

Analysing data

What have I discovered about statistics?

Key terms that I've discovered

Smart Alex's tasks

Further reading

Interesting real research

Everything You Ever Wanted to Know About Statistics (Well, Sort of)

What will this chapter tell me?

Building statistical models

Populations and samples

Simple statistical modelsGoing beyond the data

Using statistical models to test research questions

What have I discovered about statistics?

Key terms that I've discovered

Smart Alex's tasks

Further reading

Interesting real research

The R Environment

What will this chapter tell me?

Before you start

Getting started

Using R

Getting data into R

Entering data with R Commander

Using other software to enter and edit data

Saving Data

Manipulating Data

What have I discovered about statistics?

R Packages Used in This Chapter

R Functions Used in This Chapter

Key terms that I've discovered

Smart Alex's Tasks

Further reading

Exploring Data with Graphs

What will this chapter tell me?

The art of presenting data

Packages used in this chapter

Introducing ggplot2

Graphing relationships: the scatterplot

Histograms: a good way to spot obvious problems

Boxplots (box-whisker diagrams)

Density plots

Graphing means

Themes and options

What have I discovered about statistics?

R packages used in this chapter

R functions used in this chapter

Key terms that I've discovered

Smart Alex's tasks

Further reading

Interesting real research

Exploring Assumptions

What will this chapter tell me?

What are assumptions?

Assumptions of parametric data

Packages used in this chapter

The assumption of normality

Testing whether a distribution is normal

Testing for homogeneity of variance

Correcting problems in the data

What have I discovered about statistics?

R packages used in this chapter

R functions used in this chapter

Key terms that I've discovered

Smart Alex's tasks

Further reading

Correlation

What will this chapter tell me?

Looking at relationships

How do we measure relationships?

Data entry for correlation analysis

Bivariate correlation

Partial correlation

Comparing correlations

Calculating the effect size

How to report correlation coefficents

What have I discovered about statistics?

R packages used in this chapter

R functions used in this chapter

Regression

What will this chapter tell me?

An Introduction to regression

Packages used in this chapter

General procedure for regression in R

Interpreting a simple regression

Multiple regression: the basics

How accurate is my regression model?

How to do multiple regression using R Commander and R

Testing the accuracy of your regression model

Robust regression: bootstrapping

How to report multiple regression

Categorical predictors and multiple regression

What have I discovered about statistics?

R packages used in this chapter

R functions used in this chapter

Key terms that I've discovered

Smart Alex's tasks

Further reading

Interesting real research

Logistic Regression

What will this chapter tell me?

Background to logistic regression

What are the principles behind logistic regression?

Assumptions and things that can go wrong

Packages used in this chapter

Binary logistic regression: an example that will make you feel eel

How to report logistic regression

Testing assumptions: another example

Predicting several categories: multinomial logistic regression

What have I discovered about statistics?

R packages used in this chapter

R functions used in this chapter

Key terms that I've discovered

Smart Alex's tasks

Further reading

Interesting real research

Comparing Two Means

What will this chapter tell me?

Packages us

What will this chapter tell me?

What the hell am I doing here? I don't belong here

Initial observation: finding something that needs explaining

Generating theories and testing them

Data collection 1: what to measure

Data collection 2: how to measure

Analysing data

What have I discovered about statistics?

Key terms that I've discovered

Smart Alex's tasks

Further reading

Interesting real research

Everything You Ever Wanted to Know About Statistics (Well, Sort of)

What will this chapter tell me?

Building statistical models

Populations and samples

Simple statistical modelsGoing beyond the data

Using statistical models to test research questions

What have I discovered about statistics?

Key terms that I've discovered

Smart Alex's tasks

Further reading

Interesting real research

The R Environment

What will this chapter tell me?

Before you start

Getting started

Using R

Getting data into R

Entering data with R Commander

Using other software to enter and edit data

Saving Data

Manipulating Data

What have I discovered about statistics?

R Packages Used in This Chapter

R Functions Used in This Chapter

Key terms that I've discovered

Smart Alex's Tasks

Further reading

Exploring Data with Graphs

What will this chapter tell me?

The art of presenting data

Packages used in this chapter

Introducing ggplot2

Graphing relationships: the scatterplot

Histograms: a good way to spot obvious problems

Boxplots (box-whisker diagrams)

Density plots

Graphing means

Themes and options

What have I discovered about statistics?

R packages used in this chapter

R functions used in this chapter

Key terms that I've discovered

Smart Alex's tasks

Further reading

Interesting real research

Exploring Assumptions

What will this chapter tell me?

What are assumptions?

Assumptions of parametric data

Packages used in this chapter

The assumption of normality

Testing whether a distribution is normal

Testing for homogeneity of variance

Correcting problems in the data

What have I discovered about statistics?

R packages used in this chapter

R functions used in this chapter

Key terms that I've discovered

Smart Alex's tasks

Further reading

Correlation

What will this chapter tell me?

Looking at relationships

How do we measure relationships?

Data entry for correlation analysis

Bivariate correlation

Partial correlation

Comparing correlations

Calculating the effect size

How to report correlation coefficents

What have I discovered about statistics?

R packages used in this chapter

R functions used in this chapter

Regression

What will this chapter tell me?

An Introduction to regression

Packages used in this chapter

General procedure for regression in R

Interpreting a simple regression

Multiple regression: the basics

How accurate is my regression model?

How to do multiple regression using R Commander and R

Testing the accuracy of your regression model

Robust regression: bootstrapping

How to report multiple regression

Categorical predictors and multiple regression

What have I discovered about statistics?

R packages used in this chapter

R functions used in this chapter

Key terms that I've discovered

Smart Alex's tasks

Further reading

Interesting real research

Logistic Regression

What will this chapter tell me?

Background to logistic regression

What are the principles behind logistic regression?

Assumptions and things that can go wrong

Packages used in this chapter

Binary logistic regression: an example that will make you feel eel

How to report logistic regression

Testing assumptions: another example

Predicting several categories: multinomial logistic regression

What have I discovered about statistics?

R packages used in this chapter

R functions used in this chapter

Key terms that I've discovered

Smart Alex's tasks

Further reading

Interesting real research

Comparing Two Means

What will this chapter tell me?

Packages us

Lecturers - request an e-inspection copy of this text or contact your local SAGE representative to discuss your course needs.

Watch Andy Field's introductory video to Discovering Statistics Using R

Keeping the uniquely humorous and self-deprecating style that has made students across the world fall in love with Andy Field's books, Discovering Statistics Using R takes students on a journey of statistical discovery using R, a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences throughout the world.

The journey begins by explaining basic statistical and research concepts before a guided tour of the R software environment. Next you discover the importance of exploring and graphing data, before moving onto statistical tests that are the foundations of the rest of the book (for example correlation and regression). You will then stride confidently into intermediate level analyses such as ANOVA, before ending your journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help you gain the necessary conceptual understanding of what you're doing, the emphasis is on applying what you learn to playful and real-world examples that should make the experience more fun than you might expect.

Like its sister textbooks, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is augmented by a cast of characters to help the reader on their way, together with hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more.

Given this book's accessibility, fun spirit, and use of bizarre real-world research it should be essential for anyone wanting to learn about statistics using the freely-available R software.

Available with Perusall - an eBook that makes it easier to prepare for class

Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more .

Watch Andy Field's introductory video to Discovering Statistics Using R

Keeping the uniquely humorous and self-deprecating style that has made students across the world fall in love with Andy Field's books, Discovering Statistics Using R takes students on a journey of statistical discovery using R, a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences throughout the world.

The journey begins by explaining basic statistical and research concepts before a guided tour of the R software environment. Next you discover the importance of exploring and graphing data, before moving onto statistical tests that are the foundations of the rest of the book (for example correlation and regression). You will then stride confidently into intermediate level analyses such as ANOVA, before ending your journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help you gain the necessary conceptual understanding of what you're doing, the emphasis is on applying what you learn to playful and real-world examples that should make the experience more fun than you might expect.

Like its sister textbooks, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is augmented by a cast of characters to help the reader on their way, together with hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more.

Given this book's accessibility, fun spirit, and use of bizarre real-world research it should be essential for anyone wanting to learn about statistics using the freely-available R software.

Available with Perusall - an eBook that makes it easier to prepare for class

Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more .