Although databases used in many organizations have been found to contain errors, little is known about the effect of these errors on predictions made by linear regression models. The paper uses a real-world example, the prediction of the net asset values of mutual funds, to investigate the effect of data quality on linear regression models. The results of two experiments are reported. The first experiment shows that the error rate and magnitude of error in data used in model prediction negatively affect the predictive accuracy of linear regression models. The second experiment shows that the error rate and the magnitude of error in data used to build the model positively affect the predictive accuracy of linear regression models.
All findings are statistically significant.
The findings have managerial implications for users and builders of linear regression models. Turkey The last years of the millenium have witnessed an exponential growth in courses, degree and certificate programs offered on the Internet. Many universities have felt the pressure and responded to the challenge of new technologies. This paper uses the Informing Science Framework to present the institutional system established at METU, and describes the activities involved in implementing METU-Online in relation to the phases of the systems development life cycle. It then introduces the main features of METU-Online and provides an appraisal of its impact.