One Sample T Test

One Sample T Test

One Sample t Test is located under Model Studio > Statistical Analysis > One sample t Test.
Use the drag-and-drop method (or double-click on the node) to use the algorithm in the canvas. Then, Click the algorithm to view and select different properties for analysis.

Properties of One Sample t Test


The table below shows the properties of one sample t-test

FieldDescriptionRemark

Run

It allows you to run the node.

-

Explore

It allows you to explore the successfully executed node.

-

Vertical Ellipses

The available options are

  • Run till node
  • Run from node
  • Publish as a model
  • Publish code

-

Task Name

It is the name of the task selected on the workbook canvas.

You can click the text field to edit or modify the task name as required.

Features

It allows you to select the column for performing the test

Only numerical features can be selected

Population Mean

It allows you to enter a value for the population mean

-

Level of Significance

It allows you to enter the alpha value or a significance level

  • You can modify this value.
  • The value of alpha always lies between 0 and 1.
  • The value 0 interprets 100% confidence on the test. The value 1 interprets 0% confidence on the test. The system cannot guarantee both scenarios; hence, the values cannot be 0 and 1
Advanced

Alternative

It defines the alternative hypothesis

  • 3 Options are available:
    • Two-sided
    • less
    • smaller
  • The default is two-sided.

Nan Policy

It defines how to handle nan values

  • 3 Options are available
    • Propagate
    • Raise
    • Omit
  • The default is Propagate.

Keepdims

It allows to broadcast the result correctly against the input array.

-

Example of One Sample t Test

We consider the credit card balance dataset, which includes columns such as Age, balance, cards, and so on.
A snippet of input data is shown below.


We select Age as the feature and set the population mean to 55.

The result page of one sample t-test is displayed below.


From the above result, we can conclude that the sample mean is equal to the population mean.


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