The JMP Japan Division has been holding a seminar called "JMP Information Bureau" every Tuesday for a total of eight times from March to April this year. The purpose of this seminar is to convey various information about JMP in a short period of 30 minutes each time, and many more people than expected have participated.
Opening of JMP Information Bureau
The purpose of the JMP Information Office
The subtitle of this seminar is "Making JMP easier to understand and more fun." The seminar aims to focus mainly on the following:
- This is an opportunity to learn about the various functions and information of JMP.
- An opportunity to discover the joys of data analysis and statistical analysis
In addition, we provide information on JMP and statistics that is rarely or cannot be covered in regular seminars.
JMP Information Bureau Details and application page (applications accepted until April 25th)
JMP Information Bureau - Making JMP easier to understand and more fun - | JMP
At the time of writing this blog, the fourth seminar has already ended. Therefore, I have summarized the main contents that have been covered so far. If you have attended the seminar, I think that by reading this article as a review, you will be able to better retain what you have learned.
*The main contents of episodes 5 to 8 (final episode) will be posted on a separate blog after the 8th episode is over.
Episode 1 (Original broadcast 3/5, rebroadcast 3/7) Useful functions (Tips) recommended for JMP beginners
We've explained the JMP options Restart Analysis and Automatic Recalculation .
You can try again and again - Acquire usage by "restarting the analysis"
JMP includes a wide variety of sample data sets, many of which come with analysis scripts.
For example, if you look at the JMP sample data "Car Poll.jmp," you will see that various scripts have been saved. If you want to perform "multiple correspondence analysis with additional variables," how do you do it? Run the appropriate script and try the analysis again.
From the red triangle in the upper left corner of the report, select Start Over > Restart Analysis .
A window will then appear allowing you to specify columns; you will see that "Country of Origin" and "Size" have been specified as [Y, Objective Variable], and "Gender" has been specified as [Z, Additional Variable].
What happens to the analysis report when the data changes? ~ How "automatic recalculation" works ~
In JMP, you can create a mosaic plot in either the Bivariate or Graph Builder platform. For example, after creating a mosaic plot for the sample data "Car Poll.jmp" above, go back to the data table and exclude the first 20 rows.
When you remove 20 rows, the Graph Builder redraws the mosaic plot excluding the 20 rows of data. On the other hand, the Bivariate Relationships mosaic plot is not redrawn. This difference is due to whether or not Auto Recalculate is enabled.
Some platforms, such as Graph Builder in the Graph menu, have Auto Recalculate turned on by default. This means that if you exclude or change your data, those changes will be reflected in your graph. However, many platforms, such as Bivariate Relationships in the Analyze menu, have Auto Recalculate turned off by default. If your data changes, those changes will not be reflected. If you want the changes to be reflected in your graph, you must manually turn Auto Recalculate on.
Episode 2 (Original broadcast 3/12, rebroadcast 3/14) Learning statistics interactively using JMP
In JMPcontains many sample scripts that allow you to interactively learn statistical concepts. In this article, we have introduced some sample scripts that will help you understand regression analysis, correlation, confidence intervals, and the central limit theorem.
JMP sample data and scripts introduced in the seminar
Correlation, regression
- demoCorr.jsl
- Corrsim.jmp
- demoLeastSquares.jsl
In "demoLeastSquares.jsl", you can learn the concept of least squares by drawing a straight line that fits the plot points and checking the resulting sum of squares of the residuals.
Confidence interval
"Condidence.jsl" allows you to learn the concept of confidence intervals through random number simulation.
A 95% confidence interval for the mean is an interval that estimates that there is a 95% chance that the true mean of a data set falls within the interval.
The following figure shows the average5, standard deviation1From the distribution of20samples were extracted to construct a 95% confidence interval and to examine whether they contained the true population mean of 5. This process was repeated 100 times to observe whether the confidence intervals contained the true mean value of 5. Black bars indicate confidence intervals that contained 5, and red bars indicate those that did not. In this example, 95 out of 100 confidence intervals contained the population mean of 5. This is the concept of a confidence interval.
●Central limit theorem
- Sampling Distribution of Sample Means.jsl
"Sampling Distribution of Sample Means.jsl" allows you to learn the "Central Limit Theorem," an important theorem in statistics.
The central limit theorem is roughly stated as follows:
Whatever the population distribution, the sample mean can be approximated by a normal distribution.
In the example below, 25 random numbers are extracted from a uniform distribution, and their distribution is displayed as a histogram in the "Distribution of Sample Data" section in the middle. The average of these 25 numbers is the sample mean. By repeatedly extracting random numbers about 1,800 times, 1,800 sample means are obtained. The "Distribution of Sample Means" section in the bottom section visualizes the distribution of these 1,800 sample means as a histogram.
As you can see from the histogram of "Distribution of Sample Means," you can visually confirm that the distribution of sample means follows a normal distribution.
Episode 3 (Original broadcast 3/19, rebroadcast 3/21) About Excel profiles
We demonstrated the "Excel Profiler" feature, which allows you to visualize models saved in Microsoft Excel using the JMP Profiler.
- The JMP Profiler allows you to see how multiple input variables affect an output variable in a formula (model) set up in Excel.
- The Profiler has a feature called "Simulator." It can assume a distribution for X and simulate the distribution of Y using Monte Carlo simulation.
On a related note, I wrote a blog post about how to accomplish the equivalent of the Excel Profiler entirely in JMP.
How to do everything you can do with the Excel Profiler in JMP Profiler - JMP User Community
Episode 4 (Original broadcast 3/26, rebroadcast 3/28) Taylor Swift song analysis
We analyzed the words that frequently appear in the lyrics of the songs on Taylor Swift's albums (148 songs) and the factors that make the songs popular.
Through this analysis, we have demonstrated some important points to consider when analyzing data.
- Learn more and explore the contents of the data.
- Make full use of specific skills and knowledge to consider and interpret analysis results.
Below is a word cloud of the lyrics.
by Naohiro Masukawa (JMP Japan)
Naohiro Masukawa - JMP User Community
