“Teaching Statistics to People Who (Think They) Hate Statistics” webinar recording and extra Q&A

Last month, we held the webinar Teaching Statistics to People Who (Think They) Hate Statistics: Tips for Overcoming Statistics Anxiety with author Neil J. Salkind. Neil shared his strategies on reducing students’ statistics anxiety and tips on teaching students  how to understand statistical relationships, hypotheses, and significance.

If you were unable to attend the live webinar, you can view the recording above. Though Neil did not have enough time to get to all audience questions at the end of the webinar, he was happy to answer some remaining questions here.  See below to read extra insight and presentation slides.

Follow-up Q&A

How do you explain causality when a correlation exists but the variables may or may not be causal?

Well, a correlation can certainly be present when the variables are causal in their relationship, but a correlation can also exist when the two variables are simply associated but one does not cause the other. The key is to understand what amount of variance the variables share in common and use examples to illustrate such.

I teach business statistics and pursue outcome interpretation (i.e., understanding the statistical outcome for 100+ observations) to the greatest level and put little emphasis on manual calculations (i.e., having the students manually derive a standard deviation for 10 observations). Do you prefer teaching mechanical calculations over outcome interpretation?

I have student manually compute outcomes, then compute using some software program and then we talk about the interpretation of the results. I try to cover all bases and think that just using a computer to generate outcomes does not provide an understanding of the process and why it is important.

What methods do you use to show students how what they learn in class is applicable to life after college? (Particularly those who do not plan to go to graduate school or conduct research themselves.)

Well, I try to use as many diverse examples as possible form as many different fields as possible. And, since this is a course that talks lots about thinking in a new way, the thinking part can be applicable to many life events. But, please keep in mind that I never felt obligated to make this relevant to student who think it is not. My job is to motivate them to learn the material.

I teach the same introductory statistics online and in-class every semester. What kind of research topics would be available for comparison between online and in-class teaching?

The only thing I can suggest is to look in the literature regarding online teaching versus other types of presentations. I did not teach the course online so I have little info but I certainly think that there is a ton out there that would be useful.

We are an IES grant recipient for a research training program. We have eight weeks to teach quantitative and qualitative research methods, and STATISTICS! How should we prioritize the material? The program is for juniors and seniors in college.

This is an awfully short time to accomplish as much, but if I had to prioritize, I would spend six weeks on quantitative methods and the remainder on qualitative methods. I think that students are better prepared for real life jobs and experiences within a quantitative framework.

What are the best times to correlate data, i.e. power? Assumptions? Statistical testing?

I’m not sure I understand this question and what is meant by “best times.” When I introduce these during the course, I like to talk about correlation and relationships early and power after we discuss Type I error rates and what they mean. At least 40% of the course is devoted to testing and that comes in the last half of the course.

Nice presentation. I teach stats in a math department, and there is lots of anxiety at the beginning. I tell the students over and over from Day 1 that the motto is “this is a thinking class, not a math class.” This creates lots of relief, until about six weeks in, when the students realize that I have suckered them, since thinking is WAY harder than math 😉 .

This is the best advice I’ve gotten in years. Thank you.

Could you recommend one or two nice/relevant YouTube or SAGE Video clips to use during the first day of a graduate stats class?

There are videos in every chapter on the SAGE edge site for Statistics for People Who (Think They) Hate Statistics:  https://edge.sagepub.com/salkind6e

Is there a quick reference guide that lists key concepts and defines them?

The glossary of my statistic book does but there are such glossaries all over the Internet and on sites that specialize in statistics.

I am interested in the discussion of the flowchart he referred to.

It is available in Statistics for People Who (Think They) Hate Statistics and is used in every chapter where a statistical test is reviewed.

What kinds of instructor resources are available with these texts?  Do you think that they are suitable for graduate nursing students?

Test banks, course cartridges, lecture notes, power points, and video/multimedia links are available with both versions of Statistics for People Who (Think They) Hate Statistics. The book is used in all sorts of disciplines in graduate courses.

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