Reference no: EM131549538

Question: module 5 dq 1 Dominique

Assuming that I am interested in the relationship between Graduate Records Examinations (GRE) scores and GPAs from a large number of graduate students, using participants from one Ivy League University. The correlation analysis is statistically significant when one variable can predict the other to a reasonably reliable extent as determines mathematically in a statistical test (G.C.U, 2013). The Pearson correlation coefficient did not reach significance. This tells me that a regression analysis does not indicate any causal relationship between GRE scores and GPA scores from these Master's program graduates from this specific Ivy League University, but rather a mathematical relationship that can allow prediction of the dependent variable (outcome) to be made relatively reliably through the independent (predictive) variables within the data set (G.C.U, 2013).The reason the regression analysis was my choice is because the variables are based on theory that links these variables conceptually. In this case, it leads me to conclude that GRE scores (predictive) can relatively predict the range of the (outcome) GPA scores of the students who graduated from the electrical engineering master's degree program in this Ivy League university between 2000-2013.I do not believe that the results can be generalized because the sample was limited to one Ivy League University, and one specific Master's program from that specific school. This is not a good sample of the general University population throughout the entire U.S.A. For this to be generalized to all graduate students in electrical engineering programs across the U.S, the sample participants should be graduate students from those programs who attend different Universities throughout the U.S.A. Thereby, offering more valid and reliable results in the data and opening future opportunities for the research to be expanded upon.