Quantitative research methodologies correlational research

CORRELATIONAL RESEARCH

QUANTITATIVE RESEARCH METHODOLOGIES

Presented By: Manoj Patel

Asst. Professor

JHUNJHUNWALA BUSINESS SCHOOL

THE NATURE OF CORRELATIONAL RESEARCH

• Sometimes called associational research

• It investigates the possibility of relationships between only two variables

• Also sometimes referred to as a form of descriptive research

• Describes the degree to which two or more quantitative variables are related

PURPOSES OF CORRELATIONAL RESEARCH

• Two basic purposes

1. Help explain important human behaviors

(Explanatory Studies)

2. Predict likely outcomes

(Prediction Studies)

EXPLANOTARY STUDIES

• Researchers often investigate a number of variables they believe are related to a more complex variable.

• Unrelated variables dropped from further consideration

• Most researchers most probably trying to gain some ideas about cause and effect

• However it does not establish cause and effect

PREDICTION STUDIES

• Predict a score on one variable if a score on the other variable is known

• Determine the predictive validity of measuring instruments

• Predictor Variable; variable that is used to make the prediction

• Criterion Variable; variable about which the prediction is made

Using Scatter plots to Predict a Score

• We can use the scatter plots to find a correlation between the variables

• correlational research.pptx

A simple Prediction Equation

• Used to express the regression line

• We gain confidence in using the prediction equation to make future predictions if there is a close similarity between two results

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MORE COMPLEX CORRELATIONAL TECHNIQUES

1. Multiple Regressions; technique that enables researchers to determine a correlation between a criterion variable

• The best combination of two or more predictor variables

2. The Coefficient of Multiple Correlation

• Symbolized by R; indicates the strength of the correlation between the combination of the predictor variables and the criterion variables.

• multiple correlation.jpg

• The higher R is, the more reliable a prediction will be

3. The Coefficient of Determination

• The square of the correlation between a predictor and a criterion variable

• Indicates the percentage of the variability among the criterion scores that can be attributed to differences in the scores on the predictor variable

4. Discriminant Function Analysis

• Technique used when the technique of multiple regression cannot be used when the criterion variable is categorical

5. Factor Analysis • Technique that allows a researcher to

determine if many variables can be described by a few factors.

BASIC STEPS IN CORRELATIONAL RESEARCH

1. Problem Selection

• Three major types of problems;

a. is variable X related to variable Y?

b. how well does variable P predict variable C?

c. What are the relationship among a large number of variables and what predictions can be made?

2. Sample • Should be selected carefully, and if

possible, randomly.

• Not less than 30.

3. Instruments • Most correlational studies involve the

administration of some types of instruments (tests, questionnaire, and so on).

4. Design and Procedures • Design used quite straightforward.

5. Data Collection • Data on both variables will usually be

collected in a short time.

• Instruments used are administered in a single session or two sessions

THREATS TO INTERNAL VALIDITY

• There are some threats identified in conducting correlational research

1. Subject Characteristics • Individuals or groups have two or more

characteristics; might be a cause of variation in the other two variables.

2. Location

• Location is different for different subject

• One location may be more comfortable compared to others

3. Instrumentation

• Instrument decay; care must be taken to ensure the observers don’t become tired, bored or inattentive

• Data collector characteristics; different gender, age or ethnicity may affect specific response

4. Testing • Experience of responding to the first

instrument may influence subject responses to the second instrument

5. Mortality • Loss of subjects may make a relationship

more (or less) likely in the remaining data

EVALUATING THREATS TO INTERNAL VALIDITY

• Follows a procedure similar to the experimental research.

1. Subject Characteristics • Four of many possible characteristics

a. Severity of disability

b. Socioeconomic level of parents

c. Physical strength and coordination

d. Physical appearance

2. Mortality • Loss of subjects can be expected to reduce

magnitude of correlation

3. Location • Threats could be controlled by

independently assessing the job-site environments.

4. Instrumentation

• Instrument decay; observations should scheduled

• Data collector characteristics; interaction of data collectors and supervisors is a necessary parts

• Data collector bias; observers should have no knowledge of job ratings