So you don’t like teaching …

Hello All,

I have spoken with many people who do not care for teaching, yet find themselves in a front of a classroom. I find many people in psychology, sociology, business, and the like who love teaching, just not teaching applied statistics.

If you are such an individual, it seems that you are not alone. I read an interesting article in the Chronicle of Higher Education  where the author admits to not liking teaching, yet realizing you can not like something and still be great at it (

So, if as we enter into our break, you realize you do not like teaching … I suppose that’s OK. However, you owe it to your students to work at being great at it, nonetheless.

While on break,  here are my tips for preparing to become the best teacher you can be.

(1) Read about teaching. Obviously, posts on this blog are a great place for teachers of applied statistics. You can also review books that I discussed on a previous blog ( I also encourage you to look at the Society for the Teaching of Psychology’s web site.  One free e-book, in particular that I would like to bring to your attention is: This book, Teaching Statistics and Research Methods: Tips from ToP includes reprints of great articles on the teaching of applied statistics and research methods, and it’s FREE!

(2) Read about research, and look at the statistics involved. It is true that when I am teaching applied statistics, I have students come up with hypotheses to serve as examples for statistics problems. The only reason I am able to do this is I read a broad base of research in areas that not only interest me but also interest my students. My favorite journals for great examples for undergraduates are all Association for Psychological Science Journals, like Psychological Science, Current Directions, Perspectives in Psychological Science. APS has a new journal on clinical psychology that could also serve as a basis for great examples in the classroom. For people who are new to teaching applied statistics, write the information from the journal articles in the chapter or on your notes for a chapter. There is nothing more frustrating than standing up in the front of the classroom not being able to retrieve an example.

(3) Evaluate yourself and your students’ performance. Certainly it helps to take a couple of weeks off after grades are submitted, but it is important to evaluate how you did. What did your students learn well; what didn’t they? Examine, honestly and candidly … what happened, what coud you do that is better. Not surprising, I always find that if I get sick during a semester, even if I don’t miss any classes, my students just don’t do as well on the topics I covered while ill. We can’t be perfect, and we do need to be forgiving of ourselves, but we also have to be honest with our self assessment, and central to that self assessment is student performance. Here is a prior post on evaluating the teacher. 

(4) Revise your syllabus. I have discussed about syllabus revision in the past ( Please, don’t wait until the end of the summer to make the revisions. Your mind is fresh. You know what worked and what didn’t. If you are unsure how to make improvements, at least by identifying the areas where improvements are needed, you can start looking for new ideas. One of the best places to go (besides this blog, of course) is to colleagues who are teaching applied statistics, even in other departments. By discussing these ideas with each other, you both can benefit.

(5) Plan something new! Now everyone has to admit. We feel great when we get something new. Even a mundane pair of shoes or stockings can make a person feel better. So does trying something new when teaching. So, come up with a new pedagogical technique, completely revise your examples, or change a few activities in the classroom. Whatever you do, please … don’t start your next class doing everything just as you have in the past.
If you are looking for a “new” book and you have enjoyed reading these blogs, consider Kiess and Green (2010) Statistical Concepts for the Behavioral Sciences, 4/e with Pearson.

(6) You might as well have fun. In a previous post, I provided some tips to how to better enjoy the teaching of applied statistics(

Even if you don’t like teaching, you can have fun preparing to be the best you can be, and my guess is … you may even find yourself enjoying some of it.

Happy teaching!


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Free on-line workshop on the teaching of statistics

Hello All,

Dr. Susan Nolan from Seton Hall University will be presenting a free workshop on the teaching of statistics.

Street Stats: Using Real World Examples to Teach Scientific Literacy across the Psychology Curriculum
Featuring Dr. Susan Nolan Seton Hall University

Scientific literacy is arguably the most important skill that psychology majors acquire. It is a skill that can be strengthened through real-world, as well as psychology-based, applications. Indeed, research suggests that cognitive load is reduced when new material – say, a statistical concept like correlation – is applied to material students already understand. So, when students apply quantitative thinking to March Madness college basketball, Cosmo quizzes, fake news in The Onion, rhyme density in hip hop songs, or American Idol rankings, they are able to more readily understand the more complex concepts that comprise scientific thinking.

Susan will share

  • A framework to help your students develop their scientific
  • Engaging real-world examples that you can embed in your courses across the psychology curriculum – from Introduction to Psychology to capstone courses – to help your students become more proficient in scientific and quantitative thinking.

Susan A. Nolan is a Professor and Chair of the Department of Psychology at Seton Hall University. She earned her Ph.D. from Northwestern University, and conducts research on interpersonal consequences of mental illness and the role of gender in science, technology, engineering, and mathematics (STEM) careers, the latter funded in part by NSF. Susan enjoys teaching a wide range of courses, and integrates scientific reasoning into every course she teaches. Susan is the co-author of two statistics textbooks, and recently chaired the Statistical Literacy Presidential Taskforce of the Society for the Teaching of Psychology (STP). Susan also is the new co-author on Sandra and Don Hockenbury’s introduction to psychology textbooks.

Susan is a Vice President of STP, and an STP Master Teacher Speaker. She also is the Treasurer of Division 52 of APA (International Psychology), a representative from the American Psychological Association to the United Nations, and the incoming President-Elect of the Eastern Psychological Association.

If you have any questions about the symposium or need any assistance with registration, please contact us at

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A great resource

Hello All!

The Society for the Teaching of Psychology offers so many great resources for the teaching of applied statistics ( One important resource is Sherry Jackson and Richard Griggs’ edited e-book, “Teaching Statistics and Research Methods: Tips from TOP” The book can be accessed for free by following this link.

This book includes articles published in the journal, Teaching of Psychology, that cover several areas in the teaching of statistics including: generating data sets, illustrating statistical concepts, teaching strategies, application of technology, and helping students to develop skills in statistics.

Thanks to Jackson and Griggs, it is now easy to have a single source at your finger tips with several articles on the teaching of applied statistics.

Happy teaching!

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EPA March 2013

EPA 2013

Hello All!

I have just returned from New York City where the Eastern Psychological Association held their yearly conference. The attendance was very strong, and as in years past, there were dozens of familiar faces of professors dedicated to the teaching of applied statistics in psychology.

I, along with Susan Nolan (soon to be the president elect of EPA) and Tom Heinzen presented on Visualization in data.

I have included a copy of that presentation here.

In short, while at EPA, I reviewed three types of (no-additional cost) software that faculty could use in helping students to visualize data and master concepts in applied statistics.

One, Mathematica, has been reviewed here before (e.g,. this blog will detail how to use Mathematica Demonstration and provide an overview of the software:; this blog will review some of my favorite Mathematica Demonstrations not included in the attached presentation ).

I also talked of a novel way to use Excel as a means of exploring the graphing of data. As you all know, Excel has some interesting quirks, like how it selects an automatic axis that could highlight a difference that isn’t there, or how it will take whatever data you give it and turn it into whatever kind of graph you want, whether it makes sense or not. By having students use Excel, in a discovery learning manner (complete with Socratic type questioning) students can gain better insight not just in using Excel, but more importantly in graphing data effectively an accurately.

I also spoke of using Survey Monkey, with their ability to quickly analyze data … students can use their smart phones to collect a bunch of data very quickly, and then visualize the results.

I see the use of visual images as a critical tool for helping students to better understand applied statistics.


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APA Guidelines for Undergrads 2.0

Hello All,

Many of you are teaching applied statistics in a psychology department, so this post is for you, though the stated student learning outcomes listed below probably applied in all areas of applied statistics.  

As you may recall, the American Psychological Association adopted a set of guidelines for undergraduate psychology majors in 2007. Though statistics were not heavily specified in the 2007 guidelines, they were certainly mentioned.

Well, APA is preparing to come out with a new set of guidelines, “The APA Guidelines for the Undergraduate Psychology Major Version 2.0.” As of this writing, it is not posted on APA’s website (, but when it is, I will add the link here. In the mean time, if you are interested in having a copy, please feel free to email me. (A special thanks to Dr. Craig Wendorf from the University of Wisconsin – Stevens Point for providing me with a copy).

For now, I thought I would briefly review outcomes that are related to statistics. I encourage each of you to look at the current applied statistics class you are teaching to see … could all of these outcomes be said about students leaving your class at the end of the semester?

1.2e Students will be able to interpret simple graphs and statistical findings. (p 25)

1.2E Students will be able to describe the importance of specific statistical findings and complex graphs in the context of its level of statistical significance. (p 25)

1.4f Students will be able to select, apply, and interpret appropriate descriptive statistics to derive valid conclusions regarding research outcomes. (p 27)

1.4F Students will be able to select, apply and interpet appropriate inteferential statistics to derive valid conclusions regarding research outcomes. (p 27)

3.1f Students will be able to interpret quantitative data displayed in statistics, graphs, and tables, including statitical symbols in research reports. (p 41)

3.1F Students will be able to construct appropriate display of quantitive data in statistics, graphs, and tables.

In areas that are very closely related to applied statistics, and I’m suspecting that most of you cover in your applied statistics classes we have the following outcomes.  

1.4 a Students will be able to describe various research methods used by psychologist including their respective advantages and disadvantages. (p 27)

1.4A Students will be able to evaluate the effectiveness of quantitative and qualitative research methods in addressing relevant research questions. (p 27)

1.4b Students will be able to discuss the value of experimental designs (i.e., controlled omparisons) in justifying cause-effect relationships.(p 27)

1.4B Students will be able to limit cause-effect claims to research strategies that appropriately rule out alternative explanations. (p 27)

1.4e Students will be able to explain why conclusions in psychologocial projects must be both reliable and valid.(p 27)

1.4E Students will be able to design and adopt high quality measurement strategies that enhance reliablity and validity. (p 27)

By week’s end, I, along with Nancy Biliwese from Emory, will be presenting the current draft of the recommendations from the Society of Teaching Psychology (Division 2 of APA) at the Atlanta STP Best Practices Conference. I am looking forward to sharing those outcomes with you when I can.

In the mean time, feel free to email me with student learning outcomes you feel are critical for all classes of applied statistics.

Take care!


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STP Best Practices Conference

This year’s upcoming Society for the Teaching of Psychology’s Best Practices Conference, on October 12 and 13, 2012, to be held in Altanta, Georia will be dedicated to teaching practices in statistics and research methods

I am happy to say I will be presenting there, along with Nancy Bliwise and Tom Heinzen. We will be discussing the STP Taskforce on Statistics Literacy.

Given the list of presenters, this is bound to be a great conference. I hope to see you each there.


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Eastern Psychological Conference & Association for Psychological Sciences


A call for proposals have been sent out for the Eastern Psychological Conference for March 1 – 3, 2013 in NYC. Information can be found at  To submit to EPA, you must first be a member, though it’s very reasonable and includes the cost of the registering for the conference. I am hoping to organize a symposium on the teaching of applied statistics for EPA.  If you want to be a part of that symposium, please contact me ASAP. (bgreen) (at) (esu dot edu).

STP is also co-sponsoring a conference and has a call for papers for APS’s conference in Washington DC this coming May.

I encourage you all to consider submitting research for one or both of these conferences.


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