Search

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

3.6.1 Third Party Access and Business Agreements Non-PLU parties (also known as vendors) may have access to or take possession of confidential PLU data only upon contractual agreement (commonly using the PLU Data Sharing Agreement) between the vendor and the university. Such agreements must specify the data to be accessed or transferred, how vendor (e.g. Ellucian, CBORD) access will be limited to this data alone or how only this data will be transferred to the vendor, the vendor’s security

characteristics, while the weaker electron withdrawing groups have a lower BLA and high aromatic characteristics. This data is also supported by the UV-Vis data taken of the six molecules as the lower electron withdrawing groups showed a bathochromic shift as to be expected with an increase in aromaticity of the compound. 2:55 pm - Quantitative Analysis of Lead (Pb), Arsenic (As), and Antimony (Sb) in Metallic Coatings of Children’s Toys Brandon Blanchet, Capstone Senior Seminar Consumer product toxicology is

Annual ReportingStay informed with our detailed annual reporting, which includes comprehensive data on various aspects of our university. This page features reports from two major data collection initiatives: the Common Data Set (CDS) and the Integrated Postsecondary Education Data System (IPEDS).Common Data Set (CDS)The Common Data Set (CDS) initiative is a collaborative effort among data providers in the higher education community and publishers as represented by the College Board, Peterson’s

and Student Retention at Pacific Lutheran University 3:30pm Logan Margo Data Analysis of Minority Suspension Disparities in School Districts 4:00 – 4:30pm Break 4:30pm Jackie Lindstrom Principal Components Analysis: Using Math to Extract Underlying Structures in the Iraqi Migration Survey Data 5:00pm Zhanna Kukosh Preparing Students to Succeed in Geometry 5:30pm Kioni Kamau Exploration of Causal Effects and Modeling

various science classrooms. Future studies will aim to measure correlations between Instructor Talk and key indicators of student success including mitigation of stereotype threat, enhancement of student motivation, and boosting of student self-efficacy. I am also studying quantitative aspects of the classroom environment using a tool I collaboratively developed called DART: Decibel Analysis for Research in Teaching. DART measures classroom noise and separates it into categories that indicate the

provide individual undergraduate students with introductory study not available in the regular curriculum. The title will be listed on the student term-based record as DS: followed by the specific title designated by the student. (1 to 4) CHEM 320 : Analytical Chemistry Chemical methods of quantitative analysis, including volumetric, gravimetric, and selected instrumental methods. Includes laboratory. Prerequisites: CHEM 116; MATH 140. (4) CHEM 331 : Organic Chemistry I An introduction to structure