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populations. Domain 8: Information and Healthcare Technologies Descriptor: Information and communication technologies and informatics processes are used to provide care, gather data, form information to drive decision making, and support professionals as they expand knowledge and wisdom for practice. Informatics processes and technologies are used to manage and improve the delivery of safe, high- quality, and efficient healthcare services in accordance with best practice and professional and regulatory

, corresponding to the severity of the action and ranging from a written reprimand to expulsion (for students) and/or referral to the appropriate legal authorities. The University reserves the right to access electronic communication or data (e.g., email, computer files) as it deems necessary. While the University rarely does this, at times it may be compelled to do so in the enforcement of University policies and ethics, or by an external law enforcement agency. General Use Policy Pacific Lutheran University

Frank Hewins ’86 Frank Hewins ’86 https://www.plu.edu/resolute/winter-2018/wp-content/uploads/sites/20/2017/01/frank-hewins-cover-2-1024x427.jpg 1024 427 Kari Plog '11 Kari Plog '11 https://www.plu.edu/resolute/winter-2018/wp-content/uploads/sites/20/2016/05/kari-plog-avatar.jpg January 10, 2018 February 6, 2018 A Pacific Lutheran University alumnus and a strong partner in the extended Lute family recently earned an exceptional honor from the Washington Association of School Administrators

Student Retention through Multiple Logistic Regression Analysis Meghan Bonafilia In this presentation, we will explore a data set with over 4000 observations concerning first year students at PLU and their likelihood of staying at PLU for the next year. Using logistic regression for analysis, we will review different model selection processes and explore several factors like: GPA, race, whether or not a student is first generation, whether or not a student lives on campus, and more. 2:00pm

Student Retention through Multiple Logistic Regression Analysis Meghan Bonafilia In this presentation, we will explore a data set with over 4000 observations concerning first year students at PLU and their likelihood of staying at PLU for the next year. Using logistic regression for analysis, we will review different model selection processes and explore several factors like: GPA, race, whether or not a student is first generation, whether or not a student lives on campus, and more. 2:00pm