It seems to me that a lot of requests appear in these discussions because users attempt to solve a problem or use JMP like a spreadsheet. The rows and columns in a JMP data table resemble a spreadsheet but this appearance is misleading. My intention here is to discuss ways of using JMP, interactively or scripted, that will be rewarding instead of frustrating. I hope that others will join this discussion. Maybe we can reduce the level of frustration in the future that arises from attempts to use JMP in a way that it was not intended.
First of all, a spreadsheet is oriented around a cell. A cell is a location in which to store a value or a formula. It accepts formats. It can be organized with other cells in rows and columns. It is easy to work with rows, columns, or a selection of cells, but they are still individual cells. I can put anything anywhere at any time. That behavior is convenient when working in software that is optimized for consolidating and reporting financial data. JMP, on the other hand, is software for discovery about and between variables using myriad statistical analyses and visualizations. It is oriented around the variable. A data column is a cohesive collection of values for each variable. These related values share the same meaning and, therefore, the same format and other meta-data. A row is also a cohesive collection of values that represent an observation and share row states.
Second, the data table is primarily for storing and organizing data (variables and observations) along with their meta-data. It is not responsible for any kind of analysis. The numerical and graphical analyses happen in the many specialized platforms available through the Analyze and Graph menus. The platforms work with the data table and data filters (change row states). Multiple platforms may be simultaneously opened on the same data set. Multiple platforms maybe combined into a single window when this enhances the analysis.
How else is JMP not a spreadsheet? I will be back with more ideas but it is now your turn.
No software can claim to be all things to all users. I would not expect a word processor to be good at functional data analysis nor would I expect it to be easy to teach it to do so. Many different kinds of software easily and successfully work and play together today so that we may use each of them to their best advantage.
I fully agree. I suspect that most new JMP users have basisc or bettter than basic Excel knowledge.
Therefore, in my experience, it would be important to point out the fundamental differences between JMP and Excel as soon as possible.
This would make it possible to get positive results more quickly with JMP.
Great thread @markbailey . Whenever I introduced JMP to new users I had a simple admonition that I hammered home to those in attendance. It went something like this:
There are three rules for learning JMP:
1. JMP is not Excel.
2. JMP Is Not Excel.
3. JMP IS NOT EXCEL.
Then invariably later on in the session somebody would ask the question, "How do I do 'x' like I can in Excel?" If it wasn't doable or wise in JMP, I'd refer to the three rules to remind everyone that JMP is not Excel.
On a more serious note, I thing a key difference between JMP and spreadsheet applications is the point and click, dynamic interactivity that permeates JMP and is virtually nonexistent in spreadsheet applications. JMP is designed for what I call 'nonlinear discovery'...where the user has the opportunity to move in a sequential fashion through their data and analysis posing certain questions, learning by doing, all in the context of an analysis flow. Compare and contrast this to the what I'll call the 'once and done' of a spread sheet app. Want a bar chart? Make one. Want a pie chart? Make one. etc. But that's as far as you can go. Then it's back to square one to start over. Not so in JMP.
Imaging the following. As an experienced user of JMP, you have to switch back to Excel. The main question would be, how can I do this in Excel, what I have done before in JMP.
The first thing I teach people when they're first learning JMP is using by columns with stacked data. I find this to be a good seed to show people the difference between excel and JMP.
@markbailey I think it would be great to keep this post (or a summarized post of other people's suggestions) as a sticky on this forum. This is something I find hard to get through to people who haven't really used JMP before.
I think it would be great to keep this post (or a summarized post of other people's suggestions) as a sticky on this forum. This is something I find hard to get through to people who haven't really used JMP before.
Done. We'll keep it up there for awhile.
Excel users think in terms of having to build everything they need. Because of this, they tend to use Formula Columns to generate their stats and Graph Builder to display the results. Learning that JMP Platforms can make their lives easier is a very eye opening thing for the Excel user.
Speaking of Formula Columns, another eye opening event, is the fact that JMP Formula's don't have to fit on just one line. And they can be long and complex if needed. Several times, new Excel to JMP users have remarked that they never new that more than one statement can be used in a JMP formula.
Another "Wow that's Powerful" item, is the exposure to Excel users on how you do a Vlookup in JMP using Join/Update. The simplicty of the Join/Update platforms compared to Vlookup makes JMP a real winner.
When I'm talking to people about the difference of spreadsheets and JMP (or JMP tables) I refer to the following - besides what has been said already:
One of the big advantages in JMP is that you do not have to necessarily know upfront what you will find/have at the end. You can explore your data fast and interactive and find new clues, related variables or patterns you might never have thought of. However this also requires to be open for a different mindset! You are allowed to think yourself, using standards as guidelines instead of fixed rules (as Gerrman I know what I'm talking about :D ).
Of course there is some change in how to approach an analysis, but when you managed this change the adoption of new platforms is very easy. And the best - JMP offers a huge amount of training for free via STIPS E-Learning, on-demand webcasts, tutorials in the learning library, live-webcasts, the community with all the contributors (a big thumbs up to all of you!) blogs, discussions, and discovery summit presentations, youtube channel, ... Not to forget the technical staff which is in contact with the JMP users spread all over the world.
I am not sure if this is what you are seeking, but here are a few comments.
When I teach an introductory JMP class some of the key ponts I make include:
Then another key point is to introduce stacked tables great for By analyses (Anova) vs. unstacked used for modeling and correlation. This fits the rubric of organizing or data prep for analyses.