Explain what each of these terms mean in statistical analysis. Describe how these two coefficients differ. Conclude by stating which coefficient you believe is most useful in describing relationships between research variables.
Below is a Sample Solution.
Remember! This is just a sample. You can get a custom paper from one of our expert writers.
” Correlation is the coefficient of association between two interval variables measuring the closeness of fit of data points around the regression line . ” ( Brians , 2010 , p. 412 ) ; ” An association is said to exist between two variables when knowing the value of one for a given case improves the odds of our guessing correctly the corresponding value of the second ( Brians , el at. , 2010 , p 290 ) . These two coefficients differ by examining the differences / changes in the values of one variable , the direction of any association that might exist and consider that any association ” observed among cases sampled from a larger population is in fact a characteristic of that population and not merely an artifact of the smaller and potentially unrepresentative sample ” ( Brians el at . , 2010 p. 290 ) . I think correlation coefficient would be most useful in describing relationships between research variables for example graphing the variables . According to Brians ( 2010 , p. 303 ) ” rather than using the mean of the dependent variable ( usually designated Y ) to predict the values of individual cases , we use its geometric relationship with the independent variable ( usually designated X ) for this purpose . “