How do you use JMP to standardize data?

[#1]

An assignment requires that we standardize the data for a particular variable (runtime) and see what a current value would become after standardizing the data. Any ideas on how to do this? Thanks!

[#2]

hi Rebecca,

the most trivial way would be to do a distribution of the variable and from the red triangle menu to choose save standardized as in the picture.

this will create a new column in the data table with the standardized values of the variable for each row.

otherwise you can create a new column and insert the Standardized formula manually.

in some cases (such as the fit model platform) you do not need to standardize the data prior to the analysis since you can request the standardized coefficients  in the results. to do this you right click on the parameter estimates table and ask for the Std beta under the Columns option.

good luck!

[#3]

Hi Rebecca

To add on to Ron's reply standardizing data can also be classified as centering and scaling the data.  Centering is where you subtract the mean from all values and scaling is dividing the centered data by the standard deviation.  You can build the formula for this by first doing Analyze > Distribution and getting the mean and standard deviation values for your data.  You can then make a new column and create a column formula:

Runtime value - mean value/Stdev value.

Best,

Bill

[#4 · Accepted solution]

And you can create a virtual column this way, without the need to build a formula directly:

[#5]

The "Distributional" option to standardize the column doesn't appear for me (JMP14). What version are you using?

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@ian_jmp wrote:

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@ian_jmp wrote:

And you can create a virtual column this way, without the need to build a formula directly:

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And you can create a virtual column this way, without the need to build a formula directly:

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[#6]

The Distributional feature is available in JMP 14.  Here is the documentation taken from the "Using JMP" document. The Distributional feature only appears if you right click on a numeric column.

Transform Columns
Each launch window in JMP enables you to create one or more temporary transform columns
for use in performing analyses. These transform columns are not part of the source data table
and only can be used within the context of the current launch window. Transform columns
use formulas or calculations to define the column values. Closing the launch window deletes
any transform columns.
Each column listed in the Select Columns pane of the launch window includes an icon
representing the column’s modeling type (continuous, ordinal, or nominal) and the column
name. Right-click on a column name to create a transform column using Transform, Character,
Combine, Pairwise, Aggregate, Distributional, Date Time, Random, Row, Vector, or Formula
to calculate the column’s values.
Right-click options depend on the selected column’s data type and number of columns
selected.

The "Using JMP" document is available @

     Help==>Books==>Using JMP

[#7]

In addition to solutions already offered, it sounded like you might want to use historical data to determine how to standardize new values. If so, then you simply compute and store the mean and standard deviation of the historical sample, then use this computation: (new-mean)/(standard deviation) to standardize the new value. The computation could be performed in a column formula or with a script, depending on the situation.