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QUANTITATIVE RESEARCH METHODOLOGYCorrelational Research
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Correlational Researchsometimes called "associational research"
sometimes referred to as a form of descriptive research because it describes existing relationships between variable.illustrated graphically using scatterplot
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What is a correlational research?investigates the possibility of relationships between variables
there is no manipulation of variables
describes the degree to which two or more quantitative variables are related and it does so by using a correlation coefficient
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Purposes of Correlational ResearchTo explain
clarifies understanding of important phenomena by identifying relationships among the variables
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Scatterplot showing a correlation of +1.00Positive correlation means that high scores on one variable tend to be associated with high scores ont he other variable. While low scores on one are associated with low scores on the other.
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Scatterplot showing a correlation of -1.00Negative correlation means that high scores on one variable are associated with low scores on the other variable and low scores on one are associated with high scores on the other.
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Scatterplot showing a 0 correlation
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Purposes of Correlational ResearchTo predict
if a relationship of sufficient magnitude exists between two variables, it becomes possible to predict a score on one variable if a score in the other variable is known.
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Prediction StudiesScatterplots for prediction
construct a scatterplotcalculate the regression line, which is the bais for prediction
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Prediction Studieswhere Y'1 = the predicted score on Y (criterion variable) for individual (i)X1= individual i's sore on X (the predictor variable) a and b = values calculated mathematically from the orginal scores; constants for any given data.Y'1= a + bX1Prediction equationexpress the regression line in the form of a prediction equation, which has the following form:
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Other Correlational TechniquesMultiple Regression
enables researchers to determine a correlation between a criterion variable and the best combination of two or more predictor variables
The coefficient of multiple correlation is symbolized by R. It indicates the strength of correlation between the comination of the predictor variables and the criterion variables.
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Other Correlational TechniquesThe Coefficient of Multiple Correlation
symbolized by R (multiple regression), which indicates the strength of correlation between the combination of the predictor variables and the criterion variables
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Other Correlational TechniquesThe Coefficient of Determination
the square of the correlation between a predictor and a criterion variable symbolized by r2 (simple regression)
indicates the percentage of the variability among the criterion scores that can be attributed to differences in the scores on the predictor variable
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Other Correlational TechniquesThe Discriminant Function Analysis
Used when the criterion variable is categorical
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Other Correlational TechniquesThe Factor Analysis
determines whether many variables can be described by a few factors
Path Analysis
tests the likelihood of a casual connection among three or more variables
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Steps in Correlational ResearchProblem Selection
Sample Determination
Identification of Instrument Form
Design
Data Collection
Analysis and Interpretation