“Non-
Parametric
Statistical
Techniques”
Presented by:
Mr. Shahid Iqbal Kahloon Submitted to: Professor Dr. Fahad
Reg. No:2024F-mulphd-edu-003
Class: PhD Education
Session:Fall2024-27
, Introduction
Non-parametric statistical techniques makes minimal assumptions
about the underlying distribution of the data being studied.
Apply in following conditions:
When the assumptions of parametric tests are violated
If two samples come from the same or different
distributions
For analyzing sample results from a non-normal
distribution
When the boundary conditions for the t-test for
dependent samples are no longer fulfilled
, Introduction
Key Characteristics:
Distribution-free methods
Often used for ordinal data or when
assumptions of parametric tests are not met
Applicable to small sample sizes
Advantages:
Flexibility
Validity to outliers
Parametric
Statistical
Techniques”
Presented by:
Mr. Shahid Iqbal Kahloon Submitted to: Professor Dr. Fahad
Reg. No:2024F-mulphd-edu-003
Class: PhD Education
Session:Fall2024-27
, Introduction
Non-parametric statistical techniques makes minimal assumptions
about the underlying distribution of the data being studied.
Apply in following conditions:
When the assumptions of parametric tests are violated
If two samples come from the same or different
distributions
For analyzing sample results from a non-normal
distribution
When the boundary conditions for the t-test for
dependent samples are no longer fulfilled
, Introduction
Key Characteristics:
Distribution-free methods
Often used for ordinal data or when
assumptions of parametric tests are not met
Applicable to small sample sizes
Advantages:
Flexibility
Validity to outliers
