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Quantitative Decision Making

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QUANTITATIVE DECISION MAKING

Quantitative Decision Making

Quantitative Decision Making

Correlation

Correlation is a synonym for association. Within the framework of statistics, the term correlation refers to a group of indices that are employed to describe the magnitude and nature of a relationship between two or more variables. As a measure of correlation, which is commonly referred to as a correlation coefficient, is descriptive in nature, it cannot be employed to draw conclusions with regard to a cause-effect relationship between the variables in question. To infer cause and effect, it is necessary to conduct a controlled experiment involving an experimenter-manipulated independent variable in which subjects are randomly assigned to experimental conditions. Typically, data for which a correlation coefficient is computed are also evaluated with regression analysis. The latter is a methodology for deriving an equation that can be employed to estimate or predict a subject's score on one variable from the subject's score on another variable. This entry discusses the history of correlation and measures for assessing correlation.

Analysis of the Correlation

The economic analysis work was performed using the SPSS software to help and support in developing the provided data. Nevertheless, the data elaborates the numerical that was attached with the file that helped in deriving the defined result. The data extracted from the MS Excel (*.xlsv) format and was converted into SPSS (*.spss) format.

The first variable, which was named as CustomerID, was taken as irrelevant factor was kept on one side. The other variables customer satisfaction variable was considered as a dependent variable. This dependency was based on the factors such as this variable being used as independently to make other decisions. Next, the other dependent factor considered while calculating the entire correlation factor using these numbers were Product Quality variable. Product Quality variable was also considered as a dependent variable because it certainly was based on the main dependent factor.

The other key factor, which has been highlighted in this calculation, is the Competitive Pricing formula and extracts that were attached to be formulated. The competitive pricing factor is considered as a dependent variable due to it being based on its sole.

The Pearson Product-Moment Correlation

The Pearson product-moment correlation is the most commonly encountered bivariate measure of correlation. A bivariate correlation assesses the degree of relationship between two variables. The product-moment correlation describes the degree to which a linear relationship (the linearity is assumed) exists between one variable designated as the predictor variable (represented symbolically by the letter X) and a second variable designated as the criterion variable (represented symbolically by the letter Y). The product-moment correlation is a measure of the degree to which the variables covary (i.e., vary in relation to one another). From a theoretical perspective, the product-moment correlation is the average of the products of the paired standard deviation scores of subjects on the two variables. The equation for computing the unbiased estimate of the population correlation is.

The closer a positive value of r is to +1, the stronger (i.e., more consistent) the direct relationship between the variables, and the closer ...
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