Attention teachers of statistics: Three exceptional professors at Duke University have just launched the first installment of a Coursera MOOC on Teaching Statistics: "Teaching Statistical Thinking: Part 1 Descriptive Statistics." JMP is the featured software of this course and is used in their analysis modules. This course is designed with high
After writing the post on Teaching statistics with JMP last month, I didn’t think about a follow-on post since we had so many wonderful comments. But when we heard from Roger Hoerl at Union College about the thesis his student, Keilah Creedon, wrote (using JMP for the designed experiment part),
JMP has a growing fan club of people who are passionate about the software as a great teaching tool to more easily convey statistical concepts. Colleagues on our global academic team and I pooled some comments from noteworthy educators about why they like teaching with JMP. “In the early
A contingency analysis determines whether there is a relationship between two categorical variables. A caterer, for example, might be interested in knowing whether entrée selections at an event were related to gender, given the following data: The contingency platform in JMP requires the X and Y variables to be contained
A few days ago, I showed a customer how she could use lookup tables in JMP, and I thought it would be a good idea to share this with everyone. Those of you who have used lookup tables elsewhere already know how handy they can be. For those who have
I zone out when my colleagues go on and on about North Carolina college basketball. With mascots like Blue Devils and Demon Deacons, you’d think it would be more fun to me than it is. Add to that the fact that my university days were not spent at any of
Most statistical procedures benefit from understanding the underlying population distribution, or at the very least offering reassurance that our assumptions about those distributions are valid. JMP provides a number of ways to easily explore and investigate distributional assumptions. In this post, I provide information on fitting continuous or discrete distributions
“Know Your Power” is the slogan of the first-ever Women in Statistics conference to be held in Cary, North Carolina, just across the street from SAS headquarters. The May 15-17 conference is a celebration of women in statistics, and the program promises to highlight achievements and career interests of women
Bootstrapping is a popular resampling method for estimating the sampling distribution of a statistic. While the theory behind resampling methods dates back to Sir R.A. Fisher, bootstrap resampling was first proposed by Bradley Efron in the 1970s. Bootstrapping involves repeatedly sampling from a data set, with replacement, in order to
Launched more than 20 years ago, the Aerospace Systems Design Laboratory (ASDL) at the Georgia Institute of Technology was created to fill the gap between education and industry, with the goal of fully preparing graduates to meet the needs of employers from day one. Is the mission succeeding? I recently