Author Archives: Lea Jakob

Lea Jakob is currently finishing her psychology Master’s degree at University of Zagreb, Centre for Croatian Studies. Her research interests include clinical psychology within which she is writing her masters thesis on the topic of cognitive impairment in pulmonary patients as well as music perception and cognition. Apart from her passion for research, she has a serious case of wanderlust paired with polyglotism.

How to stop being busy and become productive

With the rise of social media, potential distractions have risen to unseen levels; they dominate our daily lives. Do you check Facebook, Twitter, Snapchat, Instagram, or Email on a constant basis? Do you have an embarrassing relationship with your alarm clock’s snooze button? Do you pass on social invites, telling other people that you are too busy? As a generation, we have lost the ability to focus sharply on the task at hand; instead, we work on a multitude of things simultaneously, lamenting that we do not achieve what we seek to achieve.

Picture of a busy person on a computer (Lego).

In this post, we share useful tips, tricks, and tools for you to stay on top of your day and move quickly from task to task, accomplishing the things that matter. In addition to linking to further resources, we suggest a three stage actionable program for you to go through in order to stop being busy and start being productive. As we (Fabian and Lea, the authors of this post) have experienced first hand, making the jump from being busy to being productive — from workaholism to strictly separating work and play, from social exclusion to social inclusion — has the promising potential of increasing quality time spent with friends and family, accelerating the pace of skill development, avoiding burnouts, and leading to increased subjective well-being.

Challenges in the 21st Century

Why would one want to become more productive? In additional to personal reasons — leading a more happier, more accomplished, more balanced life — there are societal reasons. The 21st century presents us with unique challenges, and the way we tackle them will define the future of our species. The three most important challenges are the exploitation of the Earth (including climate change), income inequality (including world poverty), and the “rise of robots” which includes digitalisation and its impact on work. In this post, we want to focus on the latter and make the argument that, in order to stay lean, one needs to cultivate what Cal Newport calls Deep work habits, enabling one to quickly adapt to changing work environments. Additionally, these habits also increase the effectiveness with which we can tackle the three challenges.

Take data science as an example. Few fields move as fast as data science. In its current form, it didn’t even exist fifteen years ago (for a very short history of the field, see this). Now “data scientist” has become the “sexiest job of the 21st century”.

The job market will change dramatically in the coming years. It is predicted that many jobs will fall out of existence, being taken over by machines, and that new jobs will be created (see this study and these books). Humanity is moving at an incredibly fast pace, and each individual’s challenge is to stay sharp amidst all those developments. To do so requires the ability to quickly learn new things, and to spend time productively — the two skills which make you most employable.

Being busy vs being productive

Every day, week, and month we have a number of tasks and obligations we need to address; the way we organize the time spent on getting these done differs strongly among individuals. It is here that the distinction between being busy and being productive becomes apparent.

When thinking of someone who is busy, usually we picture someone who tries to complete a task while in the same time thinking about some other task, checking social media, email, or conversing with other people. The splitting of attention on multiple things at once, while claiming to be working on a really important task, is a dead giveaway. This causes the task at hand to take forever to be completed. Oddly enough, the extensive time this task takes to be completed need not bother a busy person. On the contrary, it provides an opportunity to talk a lot about being busy, having so much to do, having so many exams, etc. This leads to cancellations of social plans and less time for leisure activities. Too many things to do, not enough time. One gets more and more frustrated.

On the other hand, a productive person is a responsible person with a focus on setting clear, few priorities and thinking of measurable steps how to achieve her goal. While working, an intense focus and undivided attention is directed on a single activity. Keeping track of progress gives a clear idea of what has been achieved during the day and what is left for tomorrow.

The distinction between being busy and being productive is at the core of this blog post. Table 1 below gives an overview of what distinguishes these two states.

Table describing the difference between being busy and being productive

Table 1. Describes the difference between being busy and being productive.

Learning how to learn

In addition to personal productivity, which will be the focus of the remaining sections, being able to monitor one’s learning progress and learning new things quickly is another very important skill. Barbara Oakley and Terrence Seijnowski have designed an online course over at Coursera called “Learning How To Learn” in which they discuss, among other things, the illusion of competence, memory techniques, and how to beat procrastination. It is the most popular, free course on Coursera and we highly recommend it.

Tips, tricks, and tools

Note that these are personal recommendations. Most of them are backed by science or common sense, but they need not work for you. This is a disclaimer: your mileage may vary.

Manage your time. Time is your most important commodity. You can’t get it back, so consider spending it wisely. To facilitate that, we highly recommend the Bullet Journal. It is an “analog tool designed for the digital world”. All you need is a notebook — we use a Leuchtturm1917, but any other would do, too — and a pen. Here is a video explaining the basics. It combines the idea of keeping track of your time and obligations while providing a space for creativity.

Schedule tasks & eat your frog first. Write down what needs to get done the next day on the evening before. Pick out your most despised task — your frog — and tackle it first thing in the morning. If you eat your frog first, there is nothing more disgusting that can happen during the day. Doing this mitigates procrastination and provides a sense of accomplishment that keeps you energy levels up.

Avoid social media. Social media and email have operantly conditioned us; we get a kick out every notification. Thousands of engineers are working on features that grab our attention and maximize the time we spent on the platforms they build (see also this fascinating interview). However, checking these platforms disrupts our workflow and thought process. They train us to despise boredom and instill in us the unfortunate need of having something occupy our attention at all times. Therefore, we recommend having fixed time points when you check email, and not spend too much time on social media before late in the afternoon or evening, when energy is low. More important tasks require attention during the day when your mind is still sharp.

We feel that quitting social media altogether is too extreme and would most likely be detrimental to our social life and productivity. However, we did remove social media apps from our phones and we limit the number of times we log onto these platforms per day. We recommend you do the same. You will very soon realize that they aren’t that important. Time is not well spent there.

Stop working. There is a time for work, and there is a time for play. We recommend setting yourself a fixed time when you stop working. This includes writing and responding to emails. Enjoy the rest of the day, read a book, learn a new skill, meet friends, rest your mind. This helps your mind wander from a focused into a diffuse mode of thinking which helps with insight problems such as “Thiss sentence contains threee errors.” If you do this, you will soon realize a boost in your overall creativity and subjective well-being. Cal Newport has structured his schedule according to this principle, calling it fixed-schedule productivity.

Build the right habits. Being productive is all about building the right habits. And building habits is hard; on average, it takes 66 days to build one, although there is great variability (see Lally et al., 2009, and here). In order to facilitate this process, we recommend Habitica, an app that gamifies destroying bad habits and building good habits; see Figure 1 below.

Figure 1. From left to right, shows the apps Habitica, Calm, and 7 Minute. The important thing is to not break the chain. This creates a psychological need for continuation. Note the selection bias here. It took me over a month to get to level 3 in Habitica. Don’t expect miracles; take small, consistent steps every day.

Workout. In order to create high quality work, you need to take care of your body; you can’t really be productive when you are not physically fit. Staying fit by finding an exercise routine that one enjoys and can manage is one of the best things we do, and we can only recommend it. Being able to climb stairs without getting out of breath is just one of the many rewards.

Meditate or go for a run. In order to increase your ability to focus and avoid distractions, we recommend meditation. For this purpose, we are using Calm, but any other meditation app, for example Headspace, yields similar results. (Of course, nothing beats meditating in a Buddhist centre.) This also helps during the day when some stressful event happens. It provides you with a few minutes to recharge, and then start into the day afresh. Going for a run, for example, does the same trick.

Someone asked a Zen Master, “How do you practice Zen?”
The master said, “When you are hungry, eat; when you are tired, sleep.”
“Isn’t that what everybody does anyway?”
The master replied, “No, no. Most people entertain a thousand desires when they eat and scheme over a thousand thoughts when they sleep.”

Powernap. This is one of the more unconventional recommendations, but it has worked wonders for our productivity. In the middle of the day, take a short power nap. It provides a boost of energy that lasts until bedtime (for more, see this).

Process versus Product. For starting to work, focusing on process rather than product is crucial. Set yourself a timer for, say, 25 minutes and then fully concentrate on the task at hand. Take a short break, and start the process again. In this way, you will focus on bursts of concentrated, deep work that bring you step by step towards your final outcome, say a finished blog post.

This approach is reminiscent of the way Beppo, the road sweeper, works in Michael Ende’s book Momo. About his work, he says

“…it’s like this. Sometimes, when you’ve a very long street ahead of you, you think how terribly long it is and feel sure you’ll never get it swept. And then you start to hurry. You work faster and faster and every time you look up there seems to be just as much left to sweep as before, and you try even harder, and you panic, and in the end you’re out of breath and have to stop — and still the street stretches away in front of you. That’s not the way to do it.

You must never think of the whole street at once, understand? You must only concentrate on the next step, the next breath, the next stroke of the broom, and the next, and the next. Nothing else.

That way you enjoy your work, which is important, because then you make a good job of it. And that’s how it ought to be.

And all at once, before you know it, you find you’ve swept the whole street clean, bit by bit. What’s more, you aren’t out of breath. That’s important, too.”

This technique is sometimes called the “Pomodoro”, and apps help achieving that abound. Although you need no app for this, apps are nice because they keep track of how many Pomodoros you have finished on a given day, providing you with a direct measure of your productivity. We can recommend the Productivity Challenge Timer.

Write down ten ideas. This recommendation comes from James Altucher, who wrote Reinvent Yourself which is an entertaining book with chapters such as “Seven things Star Wars taught me about productivity” and “The twenty things I’ve learned from Larry Page”. The habit is simple: write down ten ideas every day, on any topic. The basic rationale behind this is that creativity is a muscle, and like every other muscle, training it increases its strength. Most of the ideas will be rather useless, but that doesn’t matter. Now and then there will be a really good one. This habit probably has strong transfer effects, too, because creativity is required in many areas of life.

Read, Read, Read. There’s a saying that most people die by age 25 but aren’t put into a coffin until age 75. Reading allows your mind to continuously engage with novel ideas. We recommend Goodreads to organize and structure your reading.

Reflect on your day. Take a few minutes in the evening to reflect on your day. Keep a gratefulness journal in which you write down five things you are grateful for each day (this might also increases your overall happiness, see, e.g., here). Summarize your day in a few lines, pointing out the new things you have learned.

Does it work? Quantifying oneself

It is important to once in while take a cold, hard look into the mirror and ask: What am I doing? Am I working on things that matter, am I helping other people? Am I progressing, or am I stagnating in the comfort zone? Am I enjoying my life?

A useful habit to build is to, every evening, reflect on one’s behaviour and the things that have happened during the day. To achieve this, I (Fabian) have created a Google Form that I fill out daily. It includes, among others, questions on what I have eaten during the day, on the quality of my social interactions, on what the most important thing I have learned today; see Figure 2 below. It also asks me to summarize my day in a few lines.

Figure 2. Quantified Self questions. Every evening I reflect on the day by answering these questions. You can create your own, adapting the questions to your needs.

I have not done much with the data yet, but I know that just the process of answering the questions is very reflective and soothing. It is also valuable in the sense that, should there be too many days in which I feel bad, this will be directly reflected in the data and I can adjust my behaviour or my environment. I can wholeheartedly recommend this tiny bit of quantified self at the end of the day.

Incidentally, there is a whole community behind this idea of quantifying oneself. They go much further. As with most things, it is all about finding the right balance. It is easy to become overwhelmed when engaging with too many tools that measure your behaviour; you might end up being busy and chasing ghosts.

A 3 Stage program

In order to succeed in whatever area of life, commitment is key. Reading a blog post on productivity is the first step in a long journey towards actual behaviour change. In order to help you take this journey, we suggest three “stages”. Note that they are not necessarily sequential; you can take ideas from Stage 3 and implement them before things listed in Stage 1. The main reason behind these stages is that you should avoid being overwhelmed. Take small steps and stick to them. The first two stages will probably take one or two months, while the latter will take a bit longer.

Stage 1

Stage 1 is about getting started. It is about you becoming clear of your motivation; why do you want to be productive? What are the issues that plague or annoy you in the way you currently work? We recommend that you

  • Figure out and write down your motivation for why you want to be productive
  • Become aware of your social media use
  • Enroll in and complete Learning How to Learn
  • Start using the Pomodoro technique
  • Create an account on Habitica, adding habits you want to build or destroy
  • Uninstall social media apps from your phone
  • Set yourself a time point after which you will not check email nor social media

Stage 2

Stage 2 is about staying committed and developing a healthier and more consistent lifestyle.

  • Stay committed to your habits and review your motivation
  • Review what you have accomplished during the last months
  • Develop a consistent sleep-wake cycle
  • Develop a morning ritual
  • Eat healthy food, not too much, mostly plants
  • Start to exercise regularly (at least 3x a week)
  • Start a Bullet Journal

Stage 3

Stage 3 is about exceeding what you have accomplished so far. It is about figuring out your goals and the skills you want to develop. It is about not staying in your comfort zone, about building a habit of reading a variety of books, and becoming more engaged with others. It is from other people that we can learn the most.

  • Stay committed to your habits and review your motivation
  • Review what you have accomplished during the last months
  • Figure out what skills you want to develop
  • Read Deep Work and figure out a Deep Work routine that suits you
  • Engage with others and exchange ideas and practices
  • Find mentors for the skills you want to develop (e.g., writing, programming)
  • Create an account on Goodreads and organize your reading
  • Read at least two books per month


We have started this blog post discussing the future of work. But it’s not really about work. Sure, applying the ideas we have sketched will make you more productive professionally; but it’s not about running in a hamster wheel, meeting every objective at work or churning out one paper after another. Instead, it’s about finding the right balance of work and play, engaging in meaningful activities, and enjoying life.

If you take anything from this blog post, it should be the following three points.

If you work, work hard. If you’re done, be done. This means sharply separating work from play. It is important for avoiding burning out, for creating an atmosphere in which creativity and novel ideas flourish, for enhancing your life through spending time with friends and family, and, overall, for increasing the amount of play in your life. After all, play is what makes life joyful.

Never be the smartest person in the room. This is about learning from others. Identify the skills you want to develop, and seek out mentors for those skills; mentors will rapidly speed up your learning. Additionally, hang out with people with different backgrounds. This exposes you to ideas that you would not otherwise be exposed to. It is the people who we barely know that have the capacity to change our lives the most.

Be relevant. This is the culmination of the whole post. It is about helping others and having a lasting impact. This might entail donating to the world’s poorest; being there for a friend in dire times; pushing people to expand their horizons; helping them develop in the direction they want to develop in; working on projects that have a lasting positive impact. It is about doing the things that matter.

Recommended Resources

80.000 hours
Learning How To Learn
Deep Work (or How to Become a Straight-A Student)
– Cal Newport’s fixed-schedule productivity

This post was written together with Lea Jakob and is based on a workshop we have presented at the 31st EFPSA Congress in Qakh, Azerbaijan in April — twice. The feedback we got from participants was extremely positive, and so we decided to write up the main points. This post will also act as a reminder to ourselves should we ever be lead astray and fall back into old habits.

Lea Jakob

Lea Jakob

Lea Jakob is currently finishing her psychology Master’s degree at University of Zagreb, Centre for Croatian Studies. Her research interests include clinical psychology within which she is writing her masters thesis on the topic of cognitive impairment in pulmonary patients as well as music perception and cognition. Apart from her passion for research, she has a serious case of wanderlust paired with polyglotism.

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The Statistics Hell has expanded: An interview with Prof. Andy Field

FieldDoes the mention of the word “statistics” strike fear into your heart and send shivers down your spine? The results section of your thesis seeming like that dark place one should avoid at all cost? Heteroscedasticity gives you nightmares? You dread having to explain to someone what degrees of freedom are? What is the point of using ANOVA if we can do a series of t-tests? If any of these remind you of the pain of understanding statistics, or the dread of how much more lies ahead during your studies, when all you really want is someone to explain it in a humanly understandable way—look no further. Quite a few fellow students might tell you “You should go and look at Andy Field’s books. Now, at least, I understand stats”. The “Discovering statistics using …” is a gentle, student friendly introduction to statistics. Principles are introduced at a slow pace, with plenty of workable examples so that anyone with basic maths skills will be able to digest it. Now add a lens of humor and sarcasm that will have you giggling about statistics in no time!

There is a new book!

As JEPS has been excited about introducing Bayesian statistics into the lives of more psychology students (see here, here, and here for introductions, and here for software to play around with the Bayesian approach), the idea of a new book by Andy Field—whose work many of us love and wholeheartedly recommend—which incorporates this amazing approach was thrilling news.

We used this occasion to talk to Andy Field—who is he, what motivates him, and what are his thoughts on the future of psychology?

With your new book, you expand the Statistics hell with Bayesian statistics. Why is this good news for students?


There has, for a long time, been an awareness that the traditional method of testing hypotheses (null hypothesis significance testing, NHST) has its limitations. Some of these limitations are fundamental, whereas others are more about how people apply the method rather too blindly. Bayesian approaches offer an alternative, and arguably, more logical way to look at estimation and hypothesis testing. It is not without its own critics though, and it has its own set of different issues to consider. However, it is clear that there is a groundswell of support for Bayesian approaches, and that people are going to see these methods applied more and more in scientific papers. The problem is that Bayesian methods can be quite technical, and a lot of books and papers are fairly impenetrable. It can be quite hard to make the switch (or even understand what switch you would be making).

My new book essentially tries to lay some very basic foundations. It’s not a book about Bayesian statistics, it’s a book about analysing data and fitting models and I explain both the widely used classical methods and also some basic Bayesian alternatives (primarily Bayes factors). The world is not going to go Baysian overnight, so what I’m trying to do is to provide a book that covers the material that lecturers and undergraduates want covered, but also encourages them to think about the limitations of those approaches and the alternatives available to them. Hopefully, readers will have their interest piqued enough to develop their understanding by reading more specifically Bayesian books. To answer the question then, there are two reasons why introducing Bayesian approaches is a good thing for students: (1) it will help them to understand more what options are available to them when they analyse data; and (2) published research will increasingly use Bayesian methods so it will help them to make sense of what other scientists are doing with their data.

Your books are the savior for many not-so-technical psychology students. How did you first come up with writing your classic ‘Discovering Statistics with ….’ book?

Like many PhD students I was teaching statistics and SPSS to fund my PhD. I used to enjoy the challenge of trying to come up with engaging examples, and generally being a bit silly/off the wall. The student feedback was always good, and at the time I had a lot of freedom to produce my own teaching materials. At around that time, a friend-of-a-friend Dan Wright (a cognitive psychologist who was at the time doing a postdoc at City Univerity in London) was good friends with Ziyad Marar, who now heads the SAGE publications London office but at the time was a commissioning editor. Dan had just published a stats book with SAGE and Ziyad had commissioned him to help SAGE to find new authors. I was chatting to Dan during a visit to City University, and got onto the subject of me teaching SPSS and my teaching materials and whatever and he said ‘Have you ever thought of turning those into a book?’ Of course I hadn’t because books seemed like things that ‘proper’ academics did, not me. Subsequently Dan introduced me to Ziyad, who wanted to sign me up to do the book, I was in such a state of disbelief that anyone would want to publish a book written by me that I blindly agreed. The rest is history!

As an aside, I started writing it before completing my PhD although most of it was done afterwards, and I went so over the word limit that SAGE requested that I do the typesetting myself because (1) they didn’t think it would sell much (a reasonable assumption given I was a first-time author); and (2) this would save a lot of production costs. Essentially they were trying to cut their losses (and on the flip side, this also allowed me to keep the book as it was and not have to edit it to half the size!). It is a constant source of amusement to us all how much we thought the book would be a massive failure! I guess the summary is, it happened through a lot of serendipitous events. There was no master plan. I just wrote from the heart and hoped for the best, which is pretty much what I’ve done ever since.

Questionable research practices and specifically misuse of statistical methods has been a hot topic in the last years. In your opinion, what are the critical measures that have to be taken in order to improve the situation?

Three things spring immediately to mind: (1) taking the analysis away from the researcher; (2) changing the incentive structures; (3) a shift towards estimation. I’ll elaborate on these in turn.

Psychology is a very peculiar science. It’s hard to think of many other disciplines where you are expected to be an expert theoretician in a research area and also a high-level data analyst with a detailed understanding of complex statistical models. It’s bizarre really. The average medic, for example, when doing a piece of research will get expert advice from a trials unit on planning, measurement, randomization and once the data are in they’ll be sent to the biostats unit to fit the models. In other words, they are not expected to be an expert in everything: expertise is pooled. One thing, then, that I think would help is if psychologists didn’t analyse their own data but instead they were sent to a stats expert with no vested interest in the results. That way data processing and analysis could be entirely objective.

The other thing I would immediately change in academia is the incentive structures. They are completely ****** up. The whole ‘publish or perish’ mentality does nothing but harm science and waste public money. The first thing it does it create massive incentives to publish anything regardless of how interesting it is but it also incentivises ‘significance’ because journals are far more likely to publish significant results. It also encourages (especially in junior scientists) quantity over quality, and it fosters individual rather than collective motivations. For example, promotions are all about the individual demonstrating excellence rather than them demonstrating a contribution to a collective excellence. To give an example, in my research area of child anxiety I frequently have the experience that I disappear for a while to write a stats book and ignore completely child anxiety research for, say, 6 months. When I come back and try to catch up on the state of the art, hundreds, possible thousands of new papers have come out, mostly small variations on a theme, often spread across multiple publications. The signal to noise ratio is absolutely suffocating. My feeling on whether anything profound has changed in my 6 months out of the loop is ‘absolutely not’ despite several hundred new papers. Think of the collective waste of time, money and effort to achieve ‘absolutely not’. It’s good science done by extremely clever people, but everything is so piecemeal that you can’t see the word for the trees. The meaningful contributions are lost. Of course I understand that science progresses in small steps, but it has become ridiculous, and I believe that the incentive structures mean that many researchers prioritise personal gain over science. Researchers are, of course, doing what their universities expect them to do, but I can’t help but feel that psychological science would benefit from people doing fewer studies in bigger teams to address larger questions. Even at a very basic level this would mean that sample sizes would increase dramatically in psychology (which would be a wholly good thing). For this to happen, the incentive structures need to change. Value should be maximised for working in large teams, on big problems, and for saving up results to publish in more substantial papers; contribution to grants and papers should also become more balanced regardless of whether you’re first author, last author or part of a team of 30 authors.

From a statistical point of view we have to shift away from ‘all or nothing thinking’ towards estimation. From the point of view of publishing science a reviewer should ask three questions (1) is the research answering an interesting question that genuinely advances our knowledge: (2) was it well conducted to address the question being asked – i.e. does it meet the necessary methodological standards?; and (3) what do the estimates of the effects in the model tell us about the question being asked. If we strive to answer bigger questions in larger samples then p-values really become completely irrelevant (I actually think their almost irrelevant anyway but …). Pre-registration of studies helps a lot because it forces journals to address the first two questions when deciding whether to publish, but it also helps with question 3 because by making the significance of the estimates irrelevant to the decision to publish it frees the authors to focus on estimation rather than p-values. There are differing views of course on how to estimate (Classical vs Bayes, confidence intervals vs. credibility intervals etc.) but at heart, I think a shift from p-values to estimation can only be a good thing.

At JEPS we are offering students experience in scientific publishing at an early stage of their career. What could be done at universities to make students acquainted with the scientific community already during their bachelor- or master studies?

I think that psychology, as a discipline, embeds training in academic publishing within degree and PhD programs through research dissertations and the like (although note my earlier comments about the proliferation of research papers!). Nowadays though scientists are expected to engage with many different audiences through blogs, the media and so on, we could probably do more to prepare students for that by incorporating assignments into degrees that are based on public engagement. (In fact, at Sussex – and I’m sure elsewhere –  we do have these sorts of assignments).

Statistics is the predominant modeling language in almost any science and therefore sufficient knowledge about it is the prerequisite of doing any empirical work. Despite this fact, why do you think do many psychology students are reluctant to learn statistics? What could be done in education to change this attitude? How to keep it entertaining while still getting stuff done?

This really goes back to my earlier question of whether we should expect researchers to be data analysis experts. Perhaps we shouldn’t, although if we went down the route of outsourcing data analysis then a basic understanding of processing data and the types of models that can be fit would help statisticians to communicate what they have done and why.

There are lots of barriers to learning statistics. Of course anxiety is a big one, but it’s also just a very different thing to psychology. It’s a bit like putting a geography module in an English literature degree and then asking ‘why aren’t the students interested in geography?’. The answer is simple: it’s not English literature, it’s not what they want to study. It’s the same deal. People doing a psychology degree are interested in psychology, if they were interested in data they’d have chosen a maths or stats degree. The challenge is trying to help students to realize that statistical knowledge gives you power to answer interesting questions. It’s a tool, not just in research, but in making sense in an increasingly data-driven world. Numeracy and statistics, in particular, has never been more important than it is now because of the ease with which data can be collected and, therefore, the proliferation of contexts in which data is used to communicate a message to the public.

In terms of breaking down those barriers I feel strongly that teaching should be about making your own mark. What I do is not ‘correct’ (and some students hate my teaching) it’s just what works for me and my personality. In my previous books I’ve tried to use memorable examples, use humour, and I tend to have a naturally chatty writing style. In the new book I have embedded all of the academic content into a fictional story. I’m hoping that the story will be good enough to hook people in and they’ll learn statistics almost as a by-product of reading the story. Essentially they share a journey with the main character in which he keeps having to learn about statistics. I’m hoping that if the reader invests emotionally in that character then it will help them to stay invested in his journey and invested in learning. The whole enterprise is a massive gamble, I have no idea whether it will work, but as I said before I write from my heart and hope for the best!

Incidentally if you want to know more about the book and the process of creating it, see

What was your inspiration for the examples in the book? How did you come up with Satan’s little SPSS helper and other characters? How did you become the gatekeeper of the statistics hell?


The statistics hell thing comes from the fact that I listen to a lot of heavy metal music and many bands have satanic imagery. Of course, in most cases it’s just shock tactics rather than reflecting a real philosophical position, but I guess I have become a bit habituated to it. Anyway, when I designed my website (which desperately needs an overhaul incidentally) I just thought it would be amusing to poke fun at the common notion that ‘statistics is hell’. It’s supposed to be tongue-in-cheek.

As for characters in the SPSS/R/SAS book, they come from random places really. Mostly the reasons are silly and not very interesting. A few examples: the cat is simply there to look like my own cat (who is 20 now!); the Satan’s slave was because I wanted to have something with the acronym SPSS (Satan’s Personal Statistics Slave); and Oliver Twisted flags additional content so I wanted to use the phrase ‘Please sir! Can I have some more …’ like the character Oliver Twist in the Dicken’s novel. Once I knew that, it was just a matter of making him an unhinged.

The new book, of course, is much more complicated because it is a fictional story with numerous characters with different appearances and personalities. I have basically written a novel and a statistics textbook and merged the two. Therefore, each character is a lot deeper than the faces in the SPSS book – they have personalities, histories, emotions. Consequently, they have very different influences. Then, as well as the characters the storyline and the fictional world in which the story is set were influenced by all sorts of things. I’d could write you a thesis on it! In fact, I have a file on my hard drive of ‘bits of trivia’ about the new book where I kept notes on why I did certain things, where names or personalities came from, who influence the appearance of characters or objects and so on. If the book becomes a hit then come back to me and ask what influenced specific things in the book and I can probably tell you! I also think it’s nice to have some mystery and not give away too much about why the book turned out the way it did!

If you could answer any research question, what would it be?

I’d like to discover some way to make humans more tolerant of each other and of different points of view, but possibly even more than that I’d like to discover a way that people could remain at a certain age until they felt it was time to die. Mortality is the cloud over everyone’s head, but I think immortality would probably be a curse because I think you get worn down by the changing world around you. I like to think that there’s a point where you feel that you’ve done what you wanted to do and you’re ready to go. I’d invent something that allows you to do that – just stay physically at an age you liked being, and go on until you’ve had enough. There is nothing more tragic than a life ended early, so I’d stop that.

Thank you for taking the time for this interview and sharing your insights with us. We have one last question: On a 7-point Likert scale, how much do you like 7-point Likert scale?

It depends which way around the extremes are labelled …. ;-)


For more information on ‘An adventure in statistics: the reality enigma’ see:




Lea Jakob

Lea Jakob

Lea Jakob is currently finishing her psychology Master’s degree at University of Zagreb, Centre for Croatian Studies. Her research interests include clinical psychology within which she is writing her masters thesis on the topic of cognitive impairment in pulmonary patients as well as music perception and cognition. Apart from her passion for research, she has a serious case of wanderlust paired with polyglotism.

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Editor’s Pick: Our favorite MOOCs

There used to be a time when students could attend classes at their university or in their vicinity – and that was it. Lately, the geospatial restriction has vanished with the introduction of massive open online courses (MOOC’s). This format of online courses are part of the “open education” idea, offering everyone with an internet connection an opportunity to participate in various courses, presented by more and less known institutions and universities. The concept is more or less similar for all courses: anyone can join, and lectures are available in form of a video and as lecture notes. During the course, whether it is a fixed-date or self-paced (as in you deciding when to complete tasks), you will need to take quizzes, exams, and/or written projects if you wish to complete the course. In less than 10 years, this idea has grown to include millions of users, hundreds of countries and more than a dozen universities around the world, while continuing to grow.

A few years back, most courses were free and offered certificates as a reward for course completion. Nowadays, you can participate in most courses offered, but if you wish to get a certificate, there is a fee. As with every course in universities, professors or assistants are available for your questions and there is a forum for interacting with other people enrolled. In case you aren’t confident you will be able to fully understand a course in english, some of the popular courses come subtitles. If you fall in love with the format and would like to contribute, Coursera offers the possibility of you becoming a translator.

Lifelong learning is the norm nowadays. By taking MOOC, you can gain new skills and knowledge in any area of interest or keep up with the latest trends in your field. In case you are considering a change in your career or are going to start university soon, it is a nice way to sneak a peek into what the topic entails with all the time flexibility you’d like to have and from the comfort of wherever you are.

The following courses are grouped into categories, from general introductions to specific topics that enhance your methodological toolbox. Apart from the courses the JEPS team can personally recommend you, you can find a list of currently available MOOC’s on
Introduction to psychology – University of Toronto
If you are considering studying psychology or are just interested in psychology in general and are looking for a nice and comprehensive introduction, this course is yours. It covers all topics and gives you a good overview of how psychology came to be, what fields it covers, and a student favorite—mental illness. The lectures are easy to follow, cover the main topics any good textbook would cover in a more interactive and interesting way, and include the most famous experiments in psychology.

Writing in the Sciences – Stanford University
A truly excellent course that starts explaining how to improve punctuation, sentences, and paragraphs to communicate ideas as clear as possible. It also offers incredibly helpful models for how to structure your research paper. The course makes extensive use of examples so that you can apply the techniques immediately to your own work. This course will change how you write your thesis!

Understanding the Brain: The Neurobiology of Everyday Life – University of Chicago
The brain is a complex system and its neurobiology is no exception. This course takes you through all the important parts of the nervous system (beyond the brain itself) involved in our everyday functioning. Each lecture includes a very well explained theory and physiology behind the topic at hand, accompanied by very interesting examples and real-life cases to give you a better understanding. Highly recommended is the lecture on strokes–from their originas, what happens to the brain during one, to consequences to a person’s functioning.

The Brain and Space – Duke University
If you have ever wondered how our brain perceives the space around and interprets the input we get from our senses into the major picture, this course will give you a very detailed image of this complex phenomenon. Even though a general understanding of neuroscience and perception is recommended, the material can be understood with some help of Wikipedia for explanation of any unknown concepts. Everything you wanted to know about vision, spatial orientation, and perception in general is here.

Programming for Everybody (Getting started with Python) – University of Michigan
First part of the five-part course on Python programming, this is a very nice and slow-paced introductory course into the world of programming. As no previous knowledge is required, everything is explained in an easily understandable manner with a lot of examples. The shining star of this course is the professor himself, whose funny remarks make the daunting task of writing code a fun experience. In case of any doubts, there is a big and very active community on the forum ready to help at any moment.

Machine learning – Stanford University
A great introductory course in machine learning. It starts with linear regression and quickly advances into more advanced topics such as model selection, neural networks, support vector machines, large scale machine learning. The course gives both a first overview over the field and teaches you hands-on machine learning skills you can immediately apply to your research!

Calculus single variable (Five-part course) – University of Pennsylvania
Most probably the best calculus course in the world. It only requires high-school math knowledge and from there on builds up a deep knowledge about calculus by using fantastic graphics and many intuitive examples. A challenging course that is worth every minute spent on!

Introduction to Neuroeconomics: How the Brain Makes Decisions – Higher School of Economics
As neuroeconomy and psychology have been gaining a lot of attention recently, this course gives a comprehensive overview of the foundations for this new hot field and the research. As this course is highly interdisciplinary, expect to learn about neuroanatomy, psychological processes, and principles of economy merging into one theory behind decision-making. From bees, monkeys, game theory, why we dislike losing above all, and group dynamics–this course covers it all.

Statistical Learning – Stanford University
An outstanding statistics course taught by two of the world’s most famous statisticians, Trevor Hastie and Rob Tibshirani. They present tough statistical concepts in an incredibly intuitive manner and provide an R-lab after each topic to make sure that you are able to apply new knowledge immediately. They provide both of their textbooks free download for download, one heavier on the math, the other more applied.

The Addicted Brain – Emory University
Navigating in the modern world includes being exposed to (mis)information about various psychoactive substances. As having the information backed by scientific research is less biased and solid, this should be the place to learn about this topic. The course goes through all major addictive substances: from the more legal ones like alcohol, nicotine, and caffeine; medication and illegal substances; along with ways in which they change the brain and affect behavior. Lastly, two lectures cover the risks of addiction along with treatments and recent policy developments.

Drugs and the Brain – CALTECH
Building on the basics of “the Addicted Brain” (I suggest taking that one prior to this one), the course goes more in depth into what happens on a molecular level in the brain the moment a drug is taken. A big part of the course requires learning the principles of psychopharmacology, which I would wholeheartedly recommend for anyone who either wants to be a clinical psychologist or is interested in how drugs for various psychiatric diagnoses work. The course goes beyond the scope of the more basic previously mentioned course by covering neurodegenerative diseases we often hear about but aren’t really sure what they entail, along with serious headaches or migraines.

Let us know if you found this helpful or if you have any tips. Maybe you’ll find some inspiration to take a course yourself while browsing the ones we have mentioned. If you have a suggestion or previous experience with this, feel free to comment below!

Lea Jakob

Lea Jakob

Lea Jakob is currently finishing her psychology Master’s degree at University of Zagreb, Centre for Croatian Studies. Her research interests include clinical psychology within which she is writing her masters thesis on the topic of cognitive impairment in pulmonary patients as well as music perception and cognition. Apart from her passion for research, she has a serious case of wanderlust paired with polyglotism.

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