Re-Envisioning the Brown University Model: Embedding A Disciplinary Writing Consultant in an Introductory U.S History Course

College writers often wish for a sympathetic reader who can offer feedback on a draft or assist during the invention or revision process. Established in 1982, the Brown University’s Writing Fellows Program was the first to formally pair small cohorts of students with a writing tutor to receive individual assistance for the duration of a course. According to the university website, today the Writing Fellows Program is a student-driven initiative in its 32nd year, in which students “work in a spirit of collegiality, helping to extend intellectual discourse beyond the classroom.” Inspired by the success of Writing Fellows Programs that have emerged across the country, the Disciplinary Writing Consultant (DWC) Program at the University of Central Florida (UCF) was designed to offer individual support to student writers without mandating participation. Diverging from the Brown model, only one DWC was embedded in a course of approximately 50 students and offered voluntary writing assistance both in class and in writing center consultations. The goal was to bring the writing center into the classroom to encourage ongoing collaborations between students, instructor and the DWC. Building and maintaining such complex partnerships in higher education is a challenge. Condon and Rutz insist that “successful WAC requires a complex partnership among faculty, administrators, writing centers, [and] faculty development programs— an infrastructure that may well support general education or first year seminar goals” (359). This assertion outlines one of the driving questions at this major research university: How can a network of partnerships between faculty, administrators, and writing consultants benefit students and support their learning? Specifically, how can this work be done effectively at the second largest public university in the country?University Writing Cente

Regression Analysis: Unified Concepts, Practical Applications, Computer Implementation

Regression Analysis: Unified Concepts, Practical Applications, Computer Implementation is a concise and innovative book that gives a complete presentation of applied regression analysis in approximately one-half the space of competing books. With only the modest prerequisite of a basic (non-calculus) statistics course this text is appropriate for the widest possible audience including college juniors, seniors and first-year graduate students in business and statistics, as well as professionals in business and industry. The book is able to accommodate this wide audience because of the unique, integrative approach that is taken to the teaching of regression analysis. Whereas other regression books cover regression in four chapters, beginning with a statistical review, followed by chapters on simple linear regression, matrix algebra and multiple regression, this book introduces regression and covers both simple linear regression and multiple regression in single cohesive chapter. This is made possible through an efficient, integrative discussion of the two techniques. Additionally, in the same chapter (Chapter Two) basic statistical and matrix algebra concepts are introduced as needed In order to facilitate instruction. This approach avoids the needless repetition that is often found in longer treatments of the subject, while serving to bring a collective focus to students of widely varying mathematical backgrounds

Experimental Design: Unified Concepts, Practical Applications, and Computer Implementation

This book is a concise and innovative book that gives a complete presentation of the design and analysis of experiments in approximately one half the space of competing books. With only the modest prerequisite of a basic (non-calculus) statistics course, this text is appropriate for the widest possible audience. Two procedures are generally used to analyze experimental design data—analysis of variance (ANOVA) and regression analysis. Because ANOVA is more intuitive, this book devotes most of its first three chapters to showing how to use ANOVA to analyze balanced (equal sample size) experimental design data. The text first discusses regression analysis at the end of Chapter 2, where regression is used to analyze data that cannot be analyzed by ANOVA: unbalanced (unequal sample size) data from two-way factorials and data from incomplete block designs. Regression is then used again in Chapter 4 to analyze data resulting from two-level fractional factorial and block confounding experiments

Essentials business of statistics

xxii, 668 p.; 29 cm

Essentials of business statistics

xxii, 665 hlm. : ilus.; tab. ; 27,5 cm