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Significance Testing Against Norms

Updated

This article explains the use of Norm flags in Harmoni for different target types: Proportional Norm (0-1), Percentage Norm (0-100%), and Value Norm (exact values). Harmoni applies Norm Significance Tests instead of standard chi-squared or t-tests for single reference differences, with green and red arrows indicating significance. Significance testing against Norms requires a personalization key.

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In this article

  1. Norm Flags
  2. Norms In Analysis
  3. Stat Testing using Norms

 

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1. Norm Flags

There are three Norm flags available in Harmoni. The flag to use depends on the nature of your target. 

  • Proportional Norm - use this flag if your target is between the values of 0 and 1. This can also be referred to as Ratio. For example, Brand Link Ratio.
  • Percentage Norm - use this flag for percentage-related values 0-100%, for example, Campaign Recall.
  • Value Norm - use this flag for exact values, for example, sales and profits.

 

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2. Norms In Analysis

In an analysis with a Norm, Harmoni will use the Norm Significance Test rather than the standard chi-squared test/t-test calculations for single reference difference calculations.

Significant differences are represented using green Green.PNG and red Red.PNG arrows. 

 

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Harmoni defaults to the standard significance test calculations (SIG) between regular cells if a standard column/row is set as a reference. The Norm (SIG) calculation is ONLY used between the reference cells and the test Norm cells.

 

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In an analysis with Multiple reference significant differences (M-SIG), the Norm significance test will not apply and will be excluded from calculations at this stage.

 

3. Statistical Testing using Norms

When a measure or measure group is flagged as a Norm item, Harmoni performs statistical testing against this target. Harmoni uses the flag to determine the significance test to use.

 

Proportions/Percentages against a Norm 

Harmoni uses one sample proportion test.

One-sample proportion test is used to test whether a sample proportion is statistically different from a hypothesized proportion. The hypothesized proportion is often called a norm or a target and is a given constant value.

For proportional norm, we add Yate’s Continuity Correction. In short, Yate's Continuity Correction adjusts the number passed to the NORM significance test a little bit, to improve the accuracy of the test. However, it makes the calculation more conservative and leads to slightly reduced statistical power

Value against a Norm

Harmoni uses a one-sample t-test.

The one-sample t-test assesses whether the mean of a sample is statistically different from a hypothesized value, for example, a specified norm or target. You would use this test for measures or averages.

Bases Used for Testing

  • If the Effective Base is enabled, the effective base from the Total row/column is used as the sample size for all Norm sig calculations (Ratio, Percentage, Value).
  • If the Effective Base is OFF, the Unweighted Count (U123) from the Total row/column is used as the sample size for all Norm sig calculations (Ratio, Percentage, Value).

Learn more about effective base.

 

Significance Testing against Norms is available via a personalization keyKeys that can be applied at the user, site (all users), or company (all users) level.. Please contact support@infotools.com for more information.

 

Where to from here?

Learn more about statistical testing:

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