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An Adventure in Statistics

An Adventure in Statistics
The Reality Enigma

Experience with SAGE edge

© 2016 | 768 pages | SAGE Publications Ltd

Shortlisted for the British Psychological Society Book Award 2017
Shortlisted for the British Book Design and Production Awards 2016
Shortlisted for the Association of Learned & Professional Society Publishers Award for Innovation in Publishing 2016

An Adventure in Statistics: The Reality Enigma by best-selling author and award-winning teacher Andy Field offers a better way to learn statistics. It combines rock-solid statistics coverage with compelling visual story-telling to address the conceptual difficulties that students learning statistics for the first time often encounter in introductory courses - guiding students away from rote memorization and toward critical thinking and problem solving. Field masterfully weaves in a unique, action-packed story starring Zach, a character who thinks like a student, processing information, and the challenges of understanding it, in the same way a statistics novice would. Illustrated with stunning graphic novel-style art and featuring Socratic dialogue, the story captivates readers as it introduces them to concepts, eliminating potential statistics anxiety. 

The book assumes no previous statistics knowledge nor does it require the use of data analysis software. It covers the material you would expect for an introductory level statistics course that Field’s other books (Discovering Statistics Using IBM SPSS Statistics and Discovering Statistics Using R) only touch on, but with a contemporary twist, laying down strong foundations for understanding classical and Bayesian approaches to data analysis. 

In doing so, it provides an unrivalled launch pad to further study, research, and inquisitiveness about the real world, equipping students with the skills to succeed in their chosen degree and which they can go on to apply in the workplace.

The Story and Main Characters

The Reality Revolution

In the City of Elpis, in the year 2100, there has been a reality revolution. Prior to the revolution, Elpis citizens were unable to see their flaws and limitations, believing themselves talented and special. This led to a self-absorbed society in which hard work and the collective good were undervalued and eroded.

To combat this, Professor Milton Grey invented the reality prism, a hat that allowed its wearers to see themselves as they really were - flaws and all. Faced with the truth, Elpis citizens revolted and destroyed and banned all reality prisms.

The Mysterious Disappearance

Zach and Alice are born soon after all the prisms have been destroyed. Zach, a musician who doesn’t understand science, and Alice, a geneticist who is also a whiz at statistics, are in love. One night, after making a world-changing discovery, Alice suddenly disappears, leaving behind a song playing on a loop and a file with her research on it.

Statistics to the Rescue!

Sensing that she might be in danger, Zach follows the clues to find her, as he realizes that the key to discovering why Alice has vanished is in her research. Alas! He must learn statistics and apply what he learns in order to overcome a number of deadly challenges and find the love of his life.

As Zach and his pocket watch, The Head, embark on their quest to find Alice, they meet Professor Milton Grey and Celia, battle zombies, cross a probability bridge, and encounter Jig:Saw, a mysterious corporation that might have something to do with Alice’s disappearance…

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Prologue: The Dying Stars
1 Why You Need Science: The Beginning and The End
1.1. Will you love me now?  
1.2. How science works  
1.2.1. The research process  
1.2.2. Science as a life skill  
1.3. Research methods  
1.3.1. Correlational research methods  
1.3.2. Experimental research methods  
1.3.3. Practice, order and randomization  
1.4. Why we need science  
2 Reporting Research, Variables and Measurement: Breaking the Law
2.1. Writing up research  
2.2. Maths and statistical notation  
2.3. Variables and measurement  
2.3.1. The conspiracy unfolds  
2.3.2. Qualitative and quantitative data  
2.3.3. Levels of measurement  
2.3.4. Measurement error  
2.3.5. Validity and reliability  
3 Summarizing Data: She Loves Me Not?
3.1. Frequency distributions  
3.1.1. Tabulated frequency distributions  
3.1.2. Grouped frequency distributions  
3.1.3. Graphical frequency distributions  
3.1.4. Idealized distributions  
3.1.5. Histograms for nominal and ordinal data  
3.2. Throwing Shapes  
4 Fitting Models (Central Tendency): Somewhere In The Middle
4.1. Statistical Models  
4.1.1. From the dead  
4.1.2. Why do we need statistical models?  
4.1.3. Sample size  
4.1.4. The one and only statistical model  
4.2. Central Tendency  
4.2.1. The mode  
4.2.2. The median  
4.2.3. The mean  
4.3. The 'fit' of the mean: variance  
4.3.1. The fit of the mean  
4.3.2. Estimating the fit of the mean from a sample  
4.3.3. Outliers and variance  
4..4. Dispersion  
4.4.1. The standard deviation as an indication of dispersion  
4.4.2. The range and interquartile range  
5 Presenting Data: Aggressive Perfector
5.1. Types of graphs  
5.2. Another perfect day  
5.3. The art of presenting data  
5.3.1. What makes a good graph?  
5.3.2. Bar graphs  
5.3.3. Line graphs  
5.3.4. Boxplots (box-whisker diagrams)  
5.3.5. Graphing relationships: the scatterplot  
5.3.6. Pie charts  
6 Z-Scores: The wolf is loose
6.1. Interpreting raw scores  
6.2. Standardizing a score  
6.3. Using z-scores to compare distributions  
6.4. Using z-scores to compare scores  
6.5. Z-scores for samples  
7 Probability: The Bridge of Death
7.1. Probability  
7.1.1. Classical probability  
7.1.2. Empirical probability  
7.2. Probability and frequency distributions  
7.2.1. The discs of death  
7.2.2. Probability density functions  
7.2.3. Probability and the normal distribution  
7.2.4. The probability of a score greater than x  
7.2.5. The probability of a score less than x: The tunnels of death  
7.2.6. The probability of a score between two values: The catapults of death  
7.3. Conditional probability: Deathscotch  
Inferential Statistics: Going Beyond the Data
8.1. Estimating parameters  
8.2. How well does a sample represent the population?  
8.2.1. Sampling distributions  
8.2.2. The standard error  
8.2.3. The central limit theorem  
8.3. Confidence Intervals  
8.3.1. Calculating confidence intervals  
8.3.2. Calculating other confidence intervals  
8.3.3. Confidence intervals in small samples  
8.4. Inferential statistics  
9 Robust Estimation: Man Without Faith or Trust
9.1. Sources of bias  
9.1.1. Extreme scores and non-normal distributions  
9.1.2. The mixed normal distribution  
9.2. A great mistake  
9.3. Reducing bias  
9.3.1. Transforming data  
9.3.2. Trimming data  
9.3.3. M-estimators  
9.3.4. Winsorizing  
9.3.5. The bootstrap  
9.4. A final point about extreme scores  
10 Hypothesis Testing: In Reality All is Void
10.1. Null hypothesis significance testing  
10.1.1. Types of hypothesis  
10.1.2. Fisher's p-value  
10.1.3. The principles of NHST  
10.1.4. Test statistics  
10.1.5. One- and two-tailed tests  
10.1.6. Type I and Type II errors  
10.1.7. Inflated error rates  
10.1.8. Statistical power  
10.1.9. Confidence intervals and statistical significance  
10.1.10. Sample size and statistical significance  
11 Modern Approaches to Theory Testing: A Careworn Heart
11.1. Problems with NHST  
11.1.1. What can you conclude from a 'significance' test?  
11.1.2. All-or-nothing thinking  
11.1.3. NHST is influenced by the intentions of the scientist  
11.2. Effect sizes  
11.2.1. Cohen's d  
11.2.2. Pearson's correlation coefficient,r  
11.2.3. The odds ratio  
11.3. Meta-analysis  
11.4. Bayesian approaches  
11.4.1. Asking a different question  
11.4.2. Bayes' theorem revisited  
11.4.3. Comparing hypothesis  
11.4.4. Benefits of bayesian approaches  
12 Assumptions: Starblind
12.1. Fitting models: bringing it all together  
12.2. Assumptions  
12.2.1. Additivity and linearity  
12.2.2. Independent errors  
12.2.3. Homoscedasticity/ homogeneity of variance  
12.2.4. Normally distributed something or other  
12.2.5. External variables  
12.2.6. Variable types  
12.2.7. Multicollinearity  
12.2.8. Non-zero variance  
12.3. Turning ever towards the sun  
13 Relationships: A Stranger's Grave
13.1. Finding relationships in categorical data  
13.1.1. Pearson's chi-square test  
13.1.2. Assumptions  
13.1.3. Fisher's exact test  
13.1.4. Yates's correction  
13.1.5. The likelihood ratio (G-test)  
13.1.6. Standardized residuals  
13.1.7. Calculating an effect size  
13.1.8. Using a computer  
13.1.9. Bayes factors for contingency tables  
13.1.10. Summary  
13.2. What evil lay dormant  
13.3. Modelling relationships  
13.3.1. Covariance  
13.3.2. Pearson's correlation coefficient  
13.3.3. The significance of the correlation coefficient  
13.3.4. Confidence intervals for r  
13.3.5. Using a computer  
13.3.6. Robust estimation of the correlation  
13.3.7. Bayesian approaches to relationships between two variables  
13.3.8. Correlation and causation  
13.3.9. Calculating the effect size  
13.4. Silent sorrow in empty boats  
14 The General Linear Model: Red Fire Coming Out From His Gills
14.1. The linear model with one predictor  
14.1.1. Estimating parameters  
14.1.2. Interpreting regression coefficients  
14.1.3. Standardized regression coefficients  
14.1.4. The standard error of b  
14.1.5. Confidence intervals for b  
14.1.6. Test statistic for b  
14.1.7. Assessing the goodness of fit  
14.1.8. Fitting a linear model using a computer  
14.1.9. When this fails  
14.2. Bias in the linear model  
14.3. A general procedure for fitting linear models  
14.4. Models with several predictors  
14.4.1. The expanded linear model  
14.4.2. Methods for entering predictors  
14.4.3. Estimating parameters  
14.4.4. Using a computer to build more complex models  
14.5. Robust regression  
14.5.1. Bayes factors for linear models  
15 Comparing Two Means: Rock or Bust
15.1. Testing differences between means: The rationale  
15.2. Means and the linear model  
15.2.1. Estimating the model parameters  
15.2.2. How the model works  
15.2.3. Testing the model parameters  
15.2.4. The independent t-test on a computer  
15.2.5. Assumptions of the model  
15.3. Everything you believe is wrong  
15.4. The paired-samples t-test  
15.4.1. The paired-samples t-test on a computer  
15.5. Alternative approaches  
15.5.1. Effect sizes  
15.5.2. Robust tests of two means  
15.5.3. Bayes factors for comparing two means  
16 Comparing Several Means: Faith in Others
16.1. General procedure for comparing means  
16.2. Comparing several means with the linear model  
16.2.1. Dummy coding  
16.2.2. The F-ratio as a test of means  
16.2.3. The total sum of squares (SSt)  
16.2.4. The model sum of squares (SSm)  
16.2.5. The residual sum of squares (SSr)  
16.2.6. Partitioning variance  
16.2.7. Mean squares  
16.2.8. The F-ratio  
16.2.9. Comparing several means using a computer  
16.3. Contrast coding  
16.3.1. Generating contrasts  
16.3.2. Devising weights  
16.3.3. Contrasts and the linear model  
16.3.4. Post hoc procedures  
16.3.5. Contrasts and post hoc tests using a computer  
16.4. Storm of memories  
16.5. Repeated-measures designs  
16.5.1. The total sum of squares, SSt  
16.5.2. The within-participant variance, SSw  
16.5.3. The model sum of squares, SSm  
16.5.4. The residual sum of squares, SSr  
16.5.5. Mean squares and the F-ratio  
16.5.6. Repeated-measures designs using a computer  
16.6. Alternative approaches  
16.6.1. Effect sizes  
16.6.2. Robust tests of several means  
16.6.3. Bayesian analysis of several means  
16.7. The invisible man  
Factorial Designs
17.1. Factorial designs  
17.2. General procedure and assumptions  
17.3. Analysing factorial designs  
17.3.1. Factorial designs and the linear model  
17.3.2. The fit of the model  
17.3.3. Factorial designs on a computer  
17.4. From the pinnacle to the pit  
17.5. Alternative approaches  
17.5.1. Calculating effect sizes  
17.5.2. Robust analysis of factorial designs  
17.5.3. Bayes factors for factorial designs  
17.6. Interpreting interaction effects  
Epilogue: The Genial Night: SI Momentum Requiris, Circumspice


Click for online resources

SAGE edge FREE Online Resources / Companion Website 

Designed to enhance each student’s learning experience, SAGE edge features carefully crafted tools and resources that encourage review, practice, and critical thinking to give students the edge they need to master course content. It also gives instructors access to course management solutions that save time and make teaching easier. 

SAGE edge for Instructors supports teaching with quality content, featuring: 

  • Test banks that provide a diverse range of customizable test items, save time, and offer a pedagogically robust way to measure your students’ understanding of the material
  • Editable, chapter-specific PowerPoint® slides featuring the tables and figures from the text to offer flexibility when creating multimedia lectures so you can customize to your exact needs 

SAGE edge for Students helps students accomplish their coursework goals in an easy-to-use, rich online learning environment that offers: 

  • Learning objectives to reinforce the most important material covered in each chapter
  • eFlashcards to strengthen understanding of key terms and concepts
  • Practice quizzes with multiple choice questions to encourage self-guided assessment and exam preparation
  • Datasets and R scripts from each chapter with hands-on exercises and problems that allow students to apply their knowledge and work through the Check your Brain problems and end-of-chapter puzzles in the text
  • Zach’s Facts from each chapter to promote targeted review of key concepts in an easy-to-access online format
  • Answers to end-of-chapter questions to allow students to track their progress
  • An online action plan highlighting all the resources available on the website that includes tips and feedback on progress through the course and materials, which allows students to individualize their learning experience
  • A bit of distraction in the form of fun quizzes and games that offer an energizing break from all that studying  
  • Links to study skills resources that appeal to different learning styles
  • Author videos and social media content designed to enhance student engagement, including access to author videos on YouTube as well as to regularly updated postings on the author’s Facebook and Twitter channels

This book is accessible and easy to read for students in their research training. The storyline and cartoons make difficult concepts easy to grasp.

Dr Jay Vickers
Health, The University of Worcester
April 9, 2018

Reading about statistics was never this exciting. I'm afraid some of the students will not appreciate it since it deviates too much from the standard textbook style so I wouldn't use it as the main course book. However, I'm definitely going to suggest it as an alternative to those who find the regular statistics textbooks too dry. It's also excellent reading for nerdy cat-lover types such as myself.

Dr Tuomo Häikiö
Department of Psychology, University of Turku
August 31, 2017

An essential read for students undertaking quantitative research for their projects. The book outlines information in an easy accessible manner and students enjoy the layout and format so that they can familiarise themselves with the approach they have chosen. Very comprehensive book.

Dr Helen Nicholas
Institute of Health & Society, Worcester University
June 13, 2017

testing review functionality

Ms Beverly Shideler
History, Five Towns College
May 24, 2017

This book is great for students in education disciplines. My students loved the entire book.

Dr Bahadir Namdar
Primary Education/ Science Education Program, Recep Tayyip Erdogan University
May 18, 2017

Brilliant read, makes statistics enjoyable

Ms Bernadette Snow
Environmental Studies, Nelson Mandela Metropolitan University
May 6, 2017

A novel approach to teaching statistics which is sure to engage the students and make it easier for them to grasp these concepts in terms of real-world problems.

Dr Dinesh Ramoo
Psychology, Cag Universitesi
April 6, 2017

It's a new Field! The book provides an unique approach to Statistics following a story and still gives insight into statistics for beginners and advanced students. I would recommend this book for anyone who has problems to really get into statistics or teachers lacking of good examples. Andy Field has a talent for making statistics interesting!

Mr Stephan Nadolny
Nursing, Bielefeld University of Applied Sciences
February 21, 2017

An Adventure in Statistics: The Reality Enigma is a modern, easy-accessible, highly readable, and useful textbook to statistical research. On the one hand, it stimulates students’ imagination in the scope of discerning links between social reality, methodology, and theory. On the other, it shows academics how to talk students through statistics and show them its research potential and limitations. Andy Field provides his readers with the comprehensive review of methods, techniques, and tools applicable to empirical studies. He introduces how to use them efficiently to explore and explain social beings, processes, and phenomena. Numerous and diverse examples illustrate well all the elements of research process. This book is worthwhile reading for all those who aim at learning statistics.

Dr Joanna Rak
Political Science , Faculty of Political Science and Journalism
December 14, 2016

I find this textbook (An Adventure in Statistics) concise, yet engaging and approachable. Well-organized recaps of important information weaved with the storyline provide the coherence for the reader. Since I am only teaching introductory level research classes for graduate students, I intend to adopt the book as an auxiliary text for those students who are interested in quantitative research and need a quick, yet sufficient introduction to the basic concepts, which will help them in conceptualizing the apriori analysis plan for their Masters' research projects or theses. The lack of formal structure for this textbook is a double-edged sword, since it is not easy to adopt this for a traditional classroom, but at the same time I see how it can be a reassuring and an easy read for someone just entering the world of stats. I would like to call this book "the gateway stats book". A brilliant effort by the author and the publishers !

Professor Javad Anjum
Education Studies Dept, Ohio University
December 10, 2016
Key features

Access the sample chapters now and see these features in action! 

  • Compelling graphic novel-style story and illustrations (by an illustrator from the Doctor Who show) introduce and apply statistics concepts gradually, keeping students engaged from the start. Students are so enthralled by the story and the characters that they “forget” how much they are learning along the way!
  • Accessible pedagogy and style directly tackle student confusion by explaining concepts in an easy-to-grasp manner. Students learn things in a sensible order and build up their knowledge; in doing so they understand the material better.
  • “Student-to-student” approach addresses the conceptual difficulties that students learning statistics for the first time encounter because the main character in the story thinks like a student, processing information and the challenges of understanding it in the same way a statistics novice would—guiding readers away from rote memorization and toward critical thinking.
  • Socratic dialogue in the story helps students understand the basics behind even the more complex statistical concepts, reinforcing critical thinking and problem-solving skills.
  • Approachable material takes the fear out of statistics and does not require math expertise, previous statistics knowledge, or use of data analysis software.
  • Beginning-of-chapter sections introduce concepts for the first time and tell students where to focus their attention.
  • In the Next Chapter, Zach Discovers (Learning Objectives) sections offer a sneak preview of what comes next.
  • Reality Check features further explain new concepts in an easy-to-understand way.
  • Check your Brain (in-chapter) exercises offer opportunities for students to apply what they’ve learned, enhancing critical thinking and problem-solving skills.
  • Figure boxes in the margins direct readers to visual representations of the material without interrupting the flow of the narrative.
  • Zach’s Facts (in-chapter summaries) recap chapter key concepts and offer another opportunity for targeted review.
  • Milton’s Meowsings (applied examples) promote critical thinking and include humorous letters (from Professor Milton Grey to Zach, the main character) giving more insight into how students could approach solving different statistical questions and how those approaches affect the outcome.
  • Key Terms at the end of each chapter help strengthen important, newly learned concepts.
  • Jig:Saw’s Puzzles give students a chance to further test their understanding of statistical concepts and work through problems at their own pace.

Sample Materials & Chapters


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