Quantitative research methodologies correlational research
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This document discusses correlational research methodologies. It defines correlational research as investigating relationships between two variables through quantitative analysis. The main purposes are explanatory, to help explain behaviors, and predictive, to predict outcomes. Key aspects covered include using scatter plots to visualize relationships and predict scores, developing prediction equations, more complex techniques like multiple regression and factor analysis, basic research steps, and threats to internal validity like subject characteristics, location, instrumentation, and mortality.
Quantitative research methodologies correlational research
- 1. CORRELATIONAL RESEARCH QUANTITATIVE RESEARCH METHODOLOGIES Presented By: Manoj Patel Asst. Professor JHUNJHUNWALA BUSINESS SCHOOL
- 2. 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
- 3. PURPOSES OF CORRELATIONAL RESEARCH • Two basic purposes 1. Help explain important human behaviors (Explanatory Studies) 2. Predict likely outcomes (Prediction Studies)
- 4. 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
- 5. 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
- 6. Using Scatter plots to Predict a Score • We can use the scatter plots to find a correlation between the variables • correlational research.pptx
- 7. 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 'Y
- 8. 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
- 9. 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
- 10. 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
- 11. 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.
- 12. 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?
- 13. 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).
- 14. 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
- 15. 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.
- 16. 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
- 17. 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
- 18. 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
- 19. 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.
- 20. 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