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Statistical Concepts in Research

Type 1 & 2 error

P value

Effect size

Power of a test

MediationModeration

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Type 1 and 2 Error

Relationship between 2 variables may or may notexist.

Research to explore this relationship may or may not

yield significant result. Thus four possibilities exist, two of which are errors.

Finding a relationship which doesnt exist is type 1error. Not finding an existing relationship is type 2

error.

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Type 1 and 2 Error

Traditionally type 1 error is considered to be more

critical than type 2 error, but consider the following

examples.

Relationship between medicine and cure Relationship between O ring and fault.

Alpha Possibility of rejecting null when its true

Beta Possibility of accepting null when its false

Why is the need for significance criteria.

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Effect Size

The actual strength of relationship between two

variables based on entire population.

Not possible to calculate exactly, but can be

estimated. As effect size increases, probability of finding a

significant relationship also increase.

Example: Size of a needle Effect size is a characteristic of individual

relationships and not depends on external factors.

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p value

Probability of getting different result than the

one achieved.

A p value of 0.05 means that if the test is

repeated 100 times, we will get the same

results 95 of the times.

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Power of a test

The probability of a test to reject a false null. OR theprobability of finding a relationship which actuallyexists. Depends on:

Beta, Effect Size and Sample.

If three of these are known, the missing one can becalculated.

Useful to estimate the sample size to achieve

significant results. Non significant result not means non existing

relationship. It may occur due to low power.

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Mediation

The mechanism through which two variables are

related.

Mediator has no effect on the direction or strength

of relationship. It only shows the path which joinsthe variables.

Examples: JS TO

JS Relationship with Spouse

What are the potential mediators

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Checking Mediation

A M B

Significant relationship between A and B

Significant relationship between A and M

Significant relationship between M and B

Significance of relationship between A-B shouldreduce significantly when M is added to the list ofindependent variables in the regression equation.

No, Partial and Full mediation.

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Moderation

Moderation comes into play when the relationshipbetween two variables is not stable and it changes itsdirection and / or strength because of an externalvariable.

Examples: Multi tasking Efficiency

?

Personality Job Performance

In moderation, the combined effect of IV and Mod Vaffects the DV. Thus IV X Mod V is a significantpredictor of DV.

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Checking Moderation.

Enter control variables and independent variable in

the regression equation. Check the R square.

Enter Mod X IV in the equation and check R square.

If R square is significant, the moderation ispresent.

Complete moderation: Direction changes

Partial moderation: Only strength changes