Application of Project Management in ISEP Promotion

I chose my Internship at the Institute for global initiatives (IGI) department of Kennesaw State University. During the January 5 to April 3, I have interning in the Office of international Services and programs (OISP).OISP is the core of IGI. My supervisor was Michele B. Miller. She is the Program Specialist & Exchange Coordinator. This year Ms. Miller has began a promotional campaign to promote the exchange student Program, especially the ISEP (International Student Exchange Programs). My job was to help her strengthen ISEP management. I accomplished this through class presentation and promotional tables at the student center of KSU. Carried out ISEP promotion and let more students know and make them be interested in this program. There are four primary activities of ISEP promotion: Activity 1: Have table in the public places of the campus. Activity 2: Making presentation in class. Activity 3: Doing orientation with students. Activity 4: Manage Facebook in the ISEP website. I have some recommendations for improving ISEP promotion. (1) We need a regular meeting (2) Information collection and data analysis (3) We need pay more attention to these factors the students often consider Suggestions to improving promotion efficiency: (1) Improving email efficiency (2) Improving the table show (3) Applying more budgets for promotion (4) More channel of promotion In my internship, I obtain experience and skill on program promotion. The knowledge I learned in my MPA class help me to understand and implement my job. My intern experience will be beneficial to my competencies and my future career

Confidence Interval Estimation of the Area under the Receiver Operating Characteristic Curve in the Presence of Measurement Error

Diagnosis of diseases is often based on biomarkers with continuous measurements. The discriminative ability of a biomarker can be depicted by a receiver operating characteristic (ROC) curve, which shows simultaneously the proportions of both ab­ normal and normal subjects correctly diagnosed at various cutoff points in the marker values. The area (A) under the ROC curve is commonly used to measure the ability of the marker to distinguish between two populations. Many biomarkers are subject to measurement error, which must be taken into account in statistical inference for A to avoid misleading results. Assuming a normal distribution for biomarker values, this thesis developed a confidence interval procedure for A adjusted for random mea­ surement error that can be quantified by an external reliability study. The basis of the new procedure is the method of variance estimates recovery. Simulation results show that this procedure outperformed the one based on the Delta method. The methodology is illustrated by a data set from a study using thiobarbituric acid reac­ tion substance to diagnose cardiovascular disease