Variance, Partitioning of variance, Sources of error variance

Important concepts- Variance, Partitioning of variance, Sources of error variance.

Kerlinger (1986) conceptualized experimental design as variance control.

Variance

Variance is the measure of the dispersion or spread of a set of scores. It describes the extent to which the scores differ from each other.

See the attachment file for practicing how to find out variance....

--measures of dispersion (spread of scores)

--statistical methods of data representation.

--Research design --variance is used for to control variance

--Researcher is analyze data to control unwanted variance.

--So, Variance control is the main theme in research design.

PRACTITIONING OF VARIANCE

--A researcher is used with 3 types of variance.

1.Experimental variance

2.Extraneous variance

3.Error variance

The main function of research design is MAXMINCON principle.

MAXIMIZE the effect of systematic variance

MINIMIZE error variance

CONTROL extraneous variance

1.Experimental variance (Systematic Variance)

--a researcher is maximize the variance of the variables related to the hypothesis.

--ie., variability in dependent variable measure to manipulate IV.

--So the experimenter MAXIMIZE variance

eg: Effects of intensity of light on visual acuity.

-manipulating three levels of light intensity i.e., 10ml, 15ml, 20ml.

2.Extraneous variance

--it is extraneous variables or relevant variables that   the experimenter tries to control relevant variables and eliminate variance produced by these variables.

-- so it requires proper CONTROL of extraneous variables.

--controlling techniques

-Randomization: random selection of exp. and con. group from population..equal chance of being represented.  eg, Randomized group design and randomized block design

-Elimination: avoiding secondary variable influence

-Matching: relavant variables

-Statistical Control: control secondary variable influence ---using analysis of covariance.

3. Error Variance:

--minimize error variance.

--is used when factors are not controlled by experimenter

-sources: attitude, motivation, need, ability etc...... differences in trials, conditions of experiment....emotional state of subject.... fatigability etc.

--statistical control is used minimize error variance

eg. repeated measures design (reduce experimental error)

    Analysis of covariance technique (to increase reliability_

SOURCES OF ERROR VARIANCE

? Poorly designed measurement instruments ( instrumental error)

? Error emanating from study subjects ( e.g., response error)

? Contextual factors that reduce a sound/ accurate measurement instrument’s

capacity to measure accurately