Warning: This isn't an easy story to listen to, as it is about life expectancy and terminal cancer (and how doctors can best convey such information to their patients). Most of this news story is dedicated to training doctors on the best way to deliver this awful news.   But Aronczyk, reporting for NPR, does tell a story that provides a good example of high-stakes applied statistics . Specifically, when explaining life expectancy to patients with terminal cancer, which measure of central tendency should be used? See the quote from the story below to understand where confusion and misunderstanding can come from measures of central tendency. " The data are typically given as a median, which is different from an average. A median is the middle of a range. So if a patient is told she has a year median survival, it means that half of similar patients will be alive at the end of a year and half will have died. It's possible that the person's cancer will advance quic...

http://www.washingtonpost.com/blogs/the-fix/wp/2014/09/29/ believe-it-or-not-some-members-of-congress-are-accountable-to-voters/ Philip Bump (writing for The Washington Post) illustrates the linear relationship between a U.S. House of Representative Representative's politics and their home district's politics. Yes, this is entirely intuitive. However, it is still a nice example of correlations/linear relationships for the reasons described below. Points for class discussion: 1) How do they go about calculating this correlation? What are the two quantitative variables that have been selected? Via legislative rankings (from the National Journal) on the y-axis and voting patterns from the House member's home district on the x-axis. 2) Several outliers' (perhaps not mathematical outliers, but instances of Representative vs. District mismatch ) careers are highlighted within the news story in order to explain why they don't align as closely with their distric...

This report from Pew  highlights the differences in opinions between the average American versus members of the American Association for the Advancement of Science (AAAS). For various topics, this graph reports the percentage of average Americans or AAAS members that endorse each science related issues as well as the gap between the two groups. Below, the yellow dots indicate the percentage of scientists that have a positive view of the issue and the blue indicate the same data for an average American. If you click on any given issue, you see more detailed information on the data. In addition to the interactive data, this report by Funk and Rainie summarizes the main findings. You can also access the original report of this data  (which contains additional information about public perception of the sciences and scientists). This could be a good tool for a research methods/statistics class in order to convince students that learning about the rigors of the scientif...

Kamenetz (reporting for NPR) talks about her book , Test , which is about the extensive use of standardized testing in our schools. Largely, this is a story about the impact these tests have had on how teachers instruct K-12 education in the US. However, a portion of the story discusses alternatives to annual testing of every student. Alternatives include using sampling to assess a school as well as numerous alternate testing methods (stealth testing, assessing child emotional well-being, portfolios, etc.). Additionally, this story touches on some of the implications of living in a Big Data society and what it is doing to our schools. I think this would be a great conversation starter for a research methods or psychometric course (especially if you are teaching such a class for a School of Education). What are we trying to assess: Individual students or teachers or schools? What are the benefits and short comings of these different kinds of assessments? Can you students come up with...

I'm an SPSS girl. I sit in my Psychology Department ivory tower and teach Introduction to Statistics via SPSS. SPSS isn't the only way to do the statistics. In fact, it is/has been losing favor among "real" statisticians. I recently had a chat with a friend who has a Ph.D. in psychology and works as a statistician. She told me that statsy job postings rarely ask for SPSS skills. Instead, they are seeking people who know R and/or Python. In order to better help our data-inclined students find work, I've gathered some information on learning R and Python. This probably isn't for every student. This probably isn't for 90% of our students. However, it may be helpful for an outstanding undergraduate or graduate student who is making noise like they want a data/research oriented career. Alternately, I think that an R class could be a really cool upper-level undergraduate elective for a select group of students. Also, if anyone is brave enough to teach thei...

Khan has been providing high-quality videos explaining...indeed...everything for a while now. Among everything are Probability and Statistics. Recently, they reorganized their content and added assessment tools as part of their #youcanlearnanything campaign in order to create self-paced lessons that are personalized to the user and include plenty of videos (of course) and personalized quizzes and feedback. 1) It requires the creation of a free account and selection of a learning topic (the screen shots below are from the Statistics and Probability course). 2) When you start a topic, you take pre-test to assess your current level. This assessment covers simple chart reading, division, and multiplication required for more advanced topics. If you struggle with this, Khan provides you with more material to improve your understanding of these topics. 3) After you complete the assessment, you receive your lesson plan. It includes the topic you select plus an additional introductory ...