# A Comparison of Course Delivery Methods: An Exercise in Experimental Economics

Save this PDF as:

Size: px
Start display at page:

Download "A Comparison of Course Delivery Methods: An Exercise in Experimental Economics"

## Transcription

4 JOURNAL OF ECONOMICS AND FINANCE EDUCATION Volume 7 Number 1 Summer students more confident about being able to handle the independent study associated with taking an on-line class. As previously mentioned, both Equations 1 and 2 are estimated by maximum likelihood estimation procedure. This procedure results in unbiased and consistent parameter estimates for Equation 1. The data employed in this study consists of students test scores and personal information. Data were collected from the registrar s office and from a survey completed by each student. There were a total of 109 students involved in the study: 31 were in the web class and 78 were in the traditional class. Summary data is provided in Table 1. Table 1 Means and Standard Deviations for Data by Type of Class VARIABLE TRADITIONAL CLASS WEB CLASS Student Performance (10.84) (10.51) Gender (.503) (.49) Race (.34) (.30) Age (1.70) (5.46) ACT (3.72) (3.67) Father (.503) (.495) Mother (.503) (.502) Crhrs Che (21.72) (29.75) Work (12.64) (15.54) Major (.495) (.508) Math (.89) (.92) Prevecon (.459) (.445) Web (.48) (.51) Cumgpa (.56) (.58) Campus (.49) (.40) Friend (.30) (.25) Internet (.66) (.72) Number Estimation Results

5 JOURNAL OF ECONOMICS AND FINANCE EDUCATION Volume 7 Number 1 Summer Table 2 provides estimation results for each independent variable associated with the class selection equation, Equation 2. The first number represents the parameter estimate and the number directly below represents the corresponding T-value. According to the empirical estimates, the coefficient on GENDER is negative and statistically significant implying that males are less likely to take an on-line class. The AGE variable s coefficient is positive and statistically significant implying that as a student s age increases the student is more likely to take an online class. The CAMPUS variable s coefficient is negative and statistically significant suggesting that students who live on campus are less likely to take an online class. The coefficient on the WORK variable is statistically significant and positive suggesting that as work hours increase students are more likely to take an online class. Finally, students with higher GPAs are less likely to take an online class. This could suggest that higher achieving students, in order to maintain their grade point average, feel more comfortable in a face-to-face class. The remaining variables, RACE, FRIEND, WEB, and INTERNET were not statistically significant at the.10 level. Table 2 Maximum Likelihood Estimates for the Class Selection Equation VARIABLE COEFFICIENT (T-STATISTICS) Intercept (-1.56) Gender a (-2.29) Race (1.151) Age a (2.02) Campus b (-1.65) Friend (0.17) Web (0.26) Internet (0.45) Work Cumgpa b (1.79) b (-1.76) Notes: a and b denote statistical significance at the.05 and.10 levels, respectively. Table 3 reports maximum likelihood estimation estimates for each independent variable as specified in student performance equation, Equation 1. The first number represents the parameter estimate and the number directly below represents the corresponding T-value. Five estimations of student performance are provided in Table 1; AVERAGE represents students average numerical grade for the entire semester and EXAMS 1-4 represent students numerical score on each semester exam. Exams 1-4 typically covered four chapters of material. In order to test for the presence of heteroscedasticity, a variation of the Breusch-Pagan test (1979) was employed. This test examines whether the values of the independent variables are related to the variance of the residuals from the regression equation. To perform the BP test one estimates the residuals from the regression equation, squares the residuals, and regresses the squared residuals on the independent variables. If the F-test confirms that the independent variables are jointly insignificant, the null hypothesis that there

6 JOURNAL OF ECONOMICS AND FINANCE EDUCATION Volume 7 Number 1 Summer is homoscedasticity cannot be rejected. This test on all five equations resulted in insignificant F-tests, thus homoscedasticity cannot be rejected. The coefficients on the course delivery variable, CLASS, are negative and statistically significant at the.05,.05 and.10 level for exams 1,2 and 3, respectively. The class variable for exam 4 is negative and significant at the.104 level. For these four student performance equations, the coefficients on the CLASS variable ranged from 5.74 to This finding suggests that students who were enrolled in the online class performed less well than students in the face-to-face class after controlling for self-selection sample bias. Since a comprehensive final exam was not given, the coefficient on the variable CLASS for the AVERAGE equation is of particular interest. The coefficient of 8.19 suggests that students average grade for the semester is almost one letter grade lower for online versus face-to-face students. Alternatively, this suggests that face-to-face delivery, ceteris paribus, results in higher student performance relative to online delivery over the entire semester. The AGE and ACT variables are positive and statistically significant in the vast majority of the five equations. This suggests that an increase in a student s age and ACT score results in higher student performance, not a surprising result. With respect to the students grade for the semester, the RACE variable was statistically significant and positive implying that white students out performed non-white students. Whereas Coates found no significant difference between males and females scores, our empirical results show that females scores are higher than males scores in four of the five performance equations. One finding of some interest is that having a previous economics class, PREVECON, had a positive and statistically significant effect only on student performance for the first semester exam. This finding is not surprising due to the fact that part of the material on the first semester exam covers material, e.g. supply and demand, that students have had in a previous economics course. Surprisingly, the impact on student performance of whether or not a parent has a college degree differs depending on gender of the parent. MOTHER is not statistically significant in any of the five equations whereas FATHER is statistically significant in three of the five equations. The variables CRHRS, CHE, and MAJOR are, for the most part, statistically insignificant in explaining student performance. The variable WORK surprisingly has a positive and significant effect in student performance exams 1 and 2, but was statistically insignificant in the remaining three student performance exams. Students math ability is positive and statistically significant for explaining average grade for the semester. It is not surprising that one s math ability has a positive impact on average performance for the semester. A correlation matrix of the independent variables suggests that multicollinearity is not a serious problem. Age and current credit hours taken exhibited the highest correlation which was a negative.5. Table 3 Maximum Likelihood Estimates for the Student Performance Equations VARIABLE AVERAGE EXAM 1 EXAM 2 EXAM 3 EXAM 4 Intercept (-1.31) (-1.25) (-0.48) (-0.82) (-1.62) Class a a a b (-3.29) (-2.60) (-3.83) (-1.89) (-1.62) Gender a a a b (-2.75) (-2.71) (-2.11) (-1.12) (-1.87) Race a a b (2.56) (1.58) (2.49) (1.43) (1.88) Age a a a a a (3.80) (2.41) (3.40) (2.66) (2.49) ACT a a a a (3.45) (3.33) (1.60) (2.71) (2.19) Father b a a

7 JOURNAL OF ECONOMICS AND FINANCE EDUCATION Volume 7 Number 1 Summer (1.92) (0.83) (0.49) (2.00) (2.09) Mother (0.94) (1.53) (-0.39) (1.32) (0.15) Crhrs a (-0.04) (0.22) (-1.41) (-1.23) (2.10) Che b b (1.83) (1.67) (1.96) (0.52) (1.08) Work a a (1.59) (2.26) (2.46) (-1.45) (0.87) Major a (-0.10) (-2.35) (0.28) (0.71) (1.26) Math a a (2.63) (1.19) (1.44) (3.99) (1.08) Prevecon b (-0.23) (1.74) (-1.32) (0.31) (-1.53) R-Square Note: a and b denote statistical significance at the.05 and.10 levels, respectively. Summary and Conclusions Experimental economics is fraught with many difficulties, notably the difficulty of holding constant other relevant variables. Moreover, a self-selection bias is introduced in cases where experiments cannot be conducted by assigning participants randomly to different treatments. Our study represents an improvement over previous studies in methodology and, unlike most studies, corrects for self-selection bias. Our evidence from comparing test score performance in the Principles of Macroeconomics courses at Western Kentucky University suggests that online delivery results in substantially lower average test scores, ceteris paribus. This finding does not, however, imply that online delivery of the Principles of Macroeconomics course should be abandoned. Such a conclusion must await further study of the costs and benefits for both online students and institutions providing online classes. In summary our findings add to the body of knowledge with respect to Thomas Russell s (1999) text, No Significant Difference Phenomenon in that our study finds a significant difference in the case of Principles of Macroeconomics when other relevant variables are controlled for and correction is made for self-selection bias. References Agarwal, Rajshree and A. Edward Day, (1998), The Impact of the Internet on Economic Education, Journal of Economic Education, 29, 2. Anstine, Jeff and Mark Skidmore, (2005), A Small Sample Study of Traditional and Online Courses with Sample Selection Adjustment, Journal of Economic Education Research. Barnow, C., G. Cain, and A. Goldberger, (1981), Issues in the Analysis of Selection Bias, Evaluation Studies Annual Review, Beverly Hills: Sage Publications. Breusch, T. S., and A. R. Pagan, (1979), A Simple Test For Heteroscedasticity And Random Coefficient Variation, Econometrica, 47, 5,

8 JOURNAL OF ECONOMICS AND FINANCE EDUCATION Volume 7 Number 1 Summer Brown, Byron and Carl Liedholm (2002), Can Web Courses Replace the Classroom in Principles of Microeconomics? American Economic Review, 92, 2, May. Coates, D., B. Humphreys, J. Kane, and M. Vachris, (2004), No Significant Difference Between Face-To-Face And Online Instruction: Evidence From Principles Of Economics, Economics of Education Review, 23. Conaway, Carrie, (2002), Virtual University: Is Online Learning Changing Higher Education? Regional Review (Federal Reserve Bank of Boston). Greene, W. H. Econometric Analysis, (2000), 4 th ed., Prentice Hall, New Jersey. McFarland, Daniel and Diane Hamilton, ( ), Factors Affecting Student Performance and Satisfaction: Online Versus Traditional Course Delivery, Journal of Computer Information Systems, Winter. McLaren, Constance, (2004), A Comparison of Student Persistence and Performance in Online and Classroom Business Statistics Experiences, Decision Sciences of Innovative Education, 2, 1. Russell, Thomas, (1999), The No Significant Difference Phenomenon, Raleigh, N.C.: North Carolina State University. Sosin, Kim, Betty Blecha, Rajshree Agarwal, Robin Bartlett and Joseph Daniel, (2004), Efficiency in the Use of Technology in Economic Education, AEA Papers and Proceedings, May. Stephenson, Kurt, Anya McGuirk, Tricia Zeh and Dixie Reaves, (2005), Comparisons of the Educational Value of Distance Delivered versus Traditional. Classroom Instruction in Introductory Agricultural Economics, Review of Agricultural Economics, 27, no. 4.

### Student Performance in Traditional vs. Online Format: Evidence from an MBA Level Introductory Economics Class

University of Connecticut DigitalCommons@UConn Economics Working Papers Department of Economics 3-1-2007 Student Performance in Traditional vs. Online Format: Evidence from an MBA Level Introductory Economics

### A Comparison of Student Learning Outcomes in Traditional and Online Personal Finance Courses

A Comparison of Student Learning Outcomes in Traditional and Online Personal Finance Courses Eddie J. Ary Associate Professor Frank D. Hickingbotham School of Business Ouachita Baptist University Arkadelphia,

### Department of Economics Working Paper Series

Department of Economics Working Paper Series Are Online Exams an Invitation to Cheat? Oskar R. Harmon University of Connecticut James Lambrinos Union University Working Paper 2006-08R March 2006, revised

### Do Proctored Exams Matter In Online Classes?

University of Connecticut DigitalCommons@UConn Economics Working Papers Department of Economics 3-1-2006 Do Proctored Exams Matter In Online Classes? Oskar R. Harmon University of Connecticut James Lambrinos

### THE EFFECTIVENESS OF VIRTUAL LEARNING IN ECONOMICS

93 THE EFFECTIVENESS OF VIRTUAL LEARNING IN ECONOMICS Neil Terry, West Texas A&M University ABSTRACT This paper presents empirical results concerning the effectiveness of Internet instruction in economics.

### TEACHING PRINCIPLES OF ECONOMICS: INTERNET VS. TRADITIONAL CLASSROOM INSTRUCTION

21 TEACHING PRINCIPLES OF ECONOMICS: INTERNET VS. TRADITIONAL CLASSROOM INSTRUCTION Doris S. Bennett, Jacksonville State University Gene L. Padgham, Jacksonville State University Cynthia S. McCarty, Jacksonville

### Department of Economics Working Paper Series

Published in Southern Economic Journal, January 2008 Department of Economics Working Paper Series Student Performance in Traditional vs. Online Format: Evidence from Introductory Economics Classes Oskar

### Can Web Courses Replace the Classroom in Principles of Microeconomics? By Byron W. Brown and Carl E. Liedholm*

Can Web Courses Replace the Classroom in Principles of Microeconomics? By Byron W. Brown and Carl E. Liedholm* The proliferation of economics courses offered partly or completely on-line (Katz and Becker,

### Do Supplemental Online Recorded Lectures Help Students Learn Microeconomics?*

Do Supplemental Online Recorded Lectures Help Students Learn Microeconomics?* Jennjou Chen and Tsui-Fang Lin Abstract With the increasing popularity of information technology in higher education, it has

### Student Success in Business Statistics

JOURNAL OF ECONOMICS AND FINANCE EDUCATION Volume 6 Number 1 Summer 2007 19 Student Success in Business Statistics Carolyn F. Rochelle and Douglas Dotterweich 1 Abstract Many universities require Business

### Teaching college microeconomics: Online vs. traditional classroom instruction

Teaching college microeconomics: Online vs. traditional classroom instruction ABSTRACT Cynthia McCarty Jacksonville State University Doris Bennett Jacksonville State University Shawn Carter Jacksonville

### Validity of Selection Criteria in Predicting MBA Success

Validity of Selection Criteria in Predicting MBA Success Terry C. Truitt Anderson University Abstract GMAT scores are found to be a robust predictor of MBA academic performance. Very little support is

### Journal of College Teaching & Learning July 2008 Volume 5, Number 7

Prerequisite Coursework As A Predictor Of Performance In A Graduate Management Course Amy McMillan-Capehart, East Carolina University Tope Adeyemi-Bello, East Carolina University ABSTRACT There have been

### No Significant Distance Between Face to Face and Online Instruction: Evidence from Principles of Economics

No Significant Distance Between Face to Face and Online Instruction: Evidence from Principles of Economics Dennis Coates University of Maryland, Baltimore County Brad R. Humphreys University of Maryland,

### 1. Suppose that a score on a final exam depends upon attendance and unobserved factors that affect exam performance (such as student ability).

Examples of Questions on Regression Analysis: 1. Suppose that a score on a final exam depends upon attendance and unobserved factors that affect exam performance (such as student ability). Then,. When

### Does Macro/Micro Course Sequencing Affect Student Performance in Principles of Economics Courses?

JOURNAL OF ECONOMICS AND FINANCE EDUCATION Volume 2 Number 2 Winter 2003 30 Does Macro/Micro Course Sequencing Affect Student Performance in Principles of Economics Courses? Dr. Andy Terry 1 and Dr. Ken

### Term paper quality of online vs. traditional students

ABSTRACT Term paper quality of online vs. traditional students Stephen Hayward West Texas A&M University Rex Pjesky West Texas A&M University This paper uses a blind grading process to test if the performance

### No Significant Distance Between Face to Face and Online Instruction: Evidence from Principles of Economics

No Significant Distance Between Face to Face and Online Instruction: Evidence from Principles of Economics Dennis Coates University of Maryland, Baltimore County Brad R. Humphreys University of Maryland,

### Evaluating Different Methods of Delivering Course Material: An Experiment in Distance Learning Using an Accounting Principles Course

Evaluating Different Methods of Delivering Course Material: An Experiment in Distance Learning Using an Accounting Principles Course Alexander R. Vamosi, Florida Institute of Technology Barbara G. Pierce,

### STUDY HABITS AND EXAMINATION PERFORMANCE IN AN ONLINE LEARNING MICROECONOMICS COURSE

STUDY HABITS AND EXAMINATION PERFORMANCE IN AN ONLINE LEARNING MICROECONOMICS COURSE Jennjou Chen, National Chengchi University Tsui-Fang Lin, National Taipei University ABSTRACT In light of the increased

### Attrition in Online and Campus Degree Programs

Attrition in Online and Campus Degree Programs Belinda Patterson East Carolina University pattersonb@ecu.edu Cheryl McFadden East Carolina University mcfaddench@ecu.edu Abstract The purpose of this study

### Online, ITV, and Traditional Delivery: Student Characteristics and Success Factors in Business Statistics

Online, ITV, and Traditional Delivery: Student Characteristics and Success Factors in Business Statistics Douglas P. Dotterweich, East Tennessee State University Carolyn F. Rochelle, East Tennessee State

### Determining Student Performance in Online Database Courses

in Online Database Courses George Garman The Metropolitan State College of Denver ABSTRACT Using data collected from 2002 to 2011, this paper analyzes the determinants of scores earned by students in a

### Determinants of Success in Economics Principles: Online vs. Face-to-Face Courses 1

Perspectives on Economic Education Research 9(1) 86-99 Journal homepage: www.isu.edu/peer/ Determinants of Success in Economics Principles: Online vs. Face-to-Face Courses 1 David Switzer a,2, Kenneth

### GRADUATE STUDENT SATISFACTION WITH AN ONLINE DISCRETE MATHEMATICS COURSE *

GRADUATE STUDENT SATISFACTION WITH AN ONLINE DISCRETE MATHEMATICS COURSE * Amber Settle DePaul University 243 S. Wabash Avenue Chicago, IL 60604 (312) 362-5324 asettle@cti.depaul.edu Chad Settle University

### Impact of attendance policies on course attendance among college students

Journal of the Scholarship of Teaching and Learning, Vol. 8, No. 3, October 2008. pp. 29-35. Impact of attendance policies on course attendance among college students Tiffany Chenneville 1 and Cary Jordan

### MARKETING EDUCATION: ONLINE VS TRADITIONAL

MARKETING EDUCATION: ONLINE VS TRADITIONAL Smith, David F. Bemidji State University dsmith@bemidjistate.edu Stephens, Barry K. Bemidji State University bstephens@bemidjistate.edu ABSTRACT Online higher

### Comparison of Student Performance in an Online with traditional Based Entry Level Engineering Course

Comparison of Student Performance in an Online with traditional Based Entry Level Engineering Course Ismail I. Orabi, Ph.D. Professor of Mechanical Engineering School of Engineering and Applied Sciences

### The Determinants of Student Performance on the Business Major Field ETS Exam: Do Community College Transfer Students Make the Grade?

The Determinants of Student Performance on the Business Major Field ETS Exam: Do Community College Transfer Students Make the Grade? Neil Terry, West Texas A&M University, USA Jean Walker, West Texas A&M

### AN INVESTIGATION OF TRADITIONAL EDUCATION VS. FULLY-ONLINE EDUCATION IN INFORMATION TECHNOLOGY

AN INVESTIGATION OF TRADITIONAL EDUCATION VS. FULLY-ONLINE EDUCATION IN INFORMATION TECHNOLOGY Johnathan Yerby Middle Georgia State University Johnathan.Yerby@maconstate.edu Kevin Floyd Middle Georgia

### Proceedings of the Annual Meeting of the American Statistical Association, August 5-9, 2001 WORK EXPERIENCE: DETERMINANT OF MBA ACADEMIC SUCCESS?

Proceedings of the Annual Meeting of the American Statistical Association, August 5-9, 2001 WORK EXPERIENCE: DETERMINANT OF MBA ACADEMIC SUCCESS? Andrew Braunstein, Iona College Hagan School of Business,

### Textbook Readability and Student Performance in. Online Introductory Corporate Finance Classes

The Journal of Educators Online-JEO July 2015 ISSN 1547-500X Vol 13 Number 2 35 Textbook Readability and Student Performance in Online Introductory Corporate Finance Classes Chien-Chih Peng, Morehead State

### Professor and Student Performance in Online Versus Traditional Introductory Finance Courses

JOURNAL OF ECONOMICS AND FINANCE EDUCATION Volume 6 Number 1 Summer 2007 40 Professor and Student Performance in Online Versus Traditional Introductory Finance Courses Joseph Farinella 1 ABSTRACT According

ONLINE VERSUS FACE-TO-FACE: DOES DELIVERY METHOD MATTER FOR UNDERGRADUATE BUSINESS SCHOOL LEARNING? Cassandra DiRienzo, Elon University Gregory Lilly, Elon University ABSTRACT Considering the significant

### A Modest Experiment Comparing HBSE Graduate Social Work Classes, On Campus and at a. Distance

A Modest Experiment 1 Running Head: Comparing On campus and Distance HBSE Courses A Modest Experiment Comparing HBSE Graduate Social Work Classes, On Campus and at a Distance A Modest Experiment 2 Abstract

### Meta-Analysis of Student Performance in Micro and Macro Economics: Online Vs. Face-To-Face Instruction

Meta-Analysis of Student Performance in Micro and Macro Economics: Online Vs. Face-To-Face Instruction Kyongsei Sohn SUNY College at Brockport Jane B. Romal SUNY College at Brockport This study presents

### Virtual Teaching in Higher Education: The New Intellectual Superhighway or Just Another Traffic Jam?

Virtual Teaching in Higher Education: The New Intellectual Superhighway or Just Another Traffic Jam? Jerald G. Schutte California State University, Northridge email - jschutte@csun.edu Abstract An experimental

### Answer: C. The strength of a correlation does not change if units change by a linear transformation such as: Fahrenheit = 32 + (5/9) * Centigrade

Statistics Quiz Correlation and Regression -- ANSWERS 1. Temperature and air pollution are known to be correlated. We collect data from two laboratories, in Boston and Montreal. Boston makes their measurements

### Regression analysis in practice with GRETL

Regression analysis in practice with GRETL Prerequisites You will need the GNU econometrics software GRETL installed on your computer (http://gretl.sourceforge.net/), together with the sample files that

### Teaching Without a Classroom: Delivering Courses Online

Teaching Without a Classroom: Delivering Courses Online Gary McDonald, Professor Department of Computer Science and Information Systems Northwest Missouri State University gary@mail.nwmissouri.edu Merry

### Emese Ivan. Teaching Sports Economics through Technology

Emese Ivan St John s University, Queens NY, USA Teaching Sports Economics through Technology Abstract: Although still in infancy, the use of the internet as a means of teaching college courses including

### Analysis of the Effectiveness of Traditional Versus Hybrid Student Performance for an Elementary Statistics Course

International Journal for the Scholarship of Teaching and Learning Volume 6 Number 2 Article 25 7-2012 Analysis of the Effectiveness of Traditional Versus Hybrid Student Performance for an Elementary Statistics

### Chapter 5: Analysis of The National Education Longitudinal Study (NELS:88)

Chapter 5: Analysis of The National Education Longitudinal Study (NELS:88) Introduction The National Educational Longitudinal Survey (NELS:88) followed students from 8 th grade in 1988 to 10 th grade in

### Journal of College Teaching & Learning July 2008 Volume 5, Number 7

Student Grade Motivation As A Determinant Of Performance On The Business Major Field ETS Exam Neil Terry, West Texas A&M University LaVelle Mills, West Texas A&M University Marc Sollosy, West Texas A&M

### Changing Distributions: How Online College Classes Alter Student and Professor Performance

Changing Distributions: How Online College Classes Alter Student and Professor Performance Eric Bettinger, Lindsay Fox, Susanna Loeb and Eric Taylor Changing Distributions: How online college classes alter

### Does the Choice of Introductory Corporate Finance Textbook Affect Student Performance?

Does the Choice of Introductory Corporate Finance Textbook Affect Student Performance? Chien-Chih Peng Morehead State University I examine whether the choice of a more readable introductory corporate finance

### ARE ONLINE COURSES CANNIBALIZING STUDENTS FROM EXISTING COURSES?

ARE ONLINE COURSES CANNIBALIZING STUDENTS FROM EXISTING COURSES? Joseph K. Cavanaugh Department of Business Wright State University, Lake Campus ABSTRACT One of the reasons most often cited for the increasing

### Brown University Department of Economics Spring 2015 ECON 1620-S01 Introduction to Econometrics Course Syllabus

Brown University Department of Economics Spring 2015 ECON 1620-S01 Introduction to Econometrics Course Syllabus Course Instructor: Dimitra Politi Office hour: Mondays 1-2pm (and by appointment) Office

### A Comparison of Online and Face-to-face Learning in Undergraduate Finance and Economic Policy Courses

Preliminary Do not quote A Comparison of Online and Face-to-face Learning in Undergraduate Finance and Economic Policy Courses JACQUES RAYNAULD MARIE-PIERRE-PELLETIER Institut d économie appliquée 1 HEC

### David Fairris Vice Provost for Undergraduate Education. Junelyn Peeples Director of Institutional Research for Undergraduate Education

Evaluation of the Impact of Participation in First Year Learning Communities on Persistence to Sophomore Year University of California, Riverside, Fall 2006 David Fairris Vice Provost for Undergraduate

### An Introduction to Statistics Course (ECOE 1302) Spring Semester 2011 Chapter 10- TWO-SAMPLE TESTS

The Islamic University of Gaza Faculty of Commerce Department of Economics and Political Sciences An Introduction to Statistics Course (ECOE 130) Spring Semester 011 Chapter 10- TWO-SAMPLE TESTS Practice

### Peer Reviewed. Abstract

Peer Reviewed The three co-authors are members of the faculty at the University of South Carolina Upstate. William R. Word and Sarah P. Rook (srook@uscupstate.edu) are Professors of Economics. Lilly M.

### ACADEMIC RISK AVERSION: AN EXPERIMENT TO INTRODUCE BUSINESS STUDENTS TO THE CONCEPTS OF RISK AND UNCERTAINTY.

Fall 2004, Vol. 3 No. 2 ACADEMIC RISK AVERSION: AN EXPERIMENT TO INTRODUCE BUSINESS STUDENTS TO THE CONCEPTS OF RISK AND UNCERTAINTY. Dr. Hilde Patron Assistant Professor of Economics College of Administration

### Research Proposal: Evaluating the Effectiveness of Online Learning as. Opposed to Traditional Classroom Delivered Instruction. Mark R.

1 Running head: Effectiveness of Online Learning Research Proposal: Evaluating the Effectiveness of Online Learning as Opposed to Traditional Classroom Delivered Instruction Mark R. Domenic University

### Title of the submission: A Modest Experiment Comparing Graduate Social Work Classes, on-campus and at A Distance

Title of the submission: A Modest Experiment Comparing Graduate Social Work Classes, on-campus and at A Distance Topic area of the submission: Distance Education Presentation format: Paper Names of the

### Examining Students Performance and Attitudes Towards the Use of Information Technology in a Virtual and Conventional Setting

The Journal of Interactive Online Learning Volume 2, Number 3, Winter 2004 www.ncolr.org ISSN: 1541-4914 Examining Students Performance and Attitudes Towards the Use of Information Technology in a Virtual

### Journal of Business & Economics Research Volume 1, Number 8

Self-Selection Bias In On-Line Accounting Courses: Student Characteristics Thomas T. Amlie, (E-mail: amliet@sunyit.edu), State University of New York Institute of Technology Abstract Over the past several

### Life in the Fast Lane: A Pre- and Post-test Comparison of MBA Performance in Accelerated versus Traditional Core Microeconomics Classes ABSTRACT

Life in the Fast Lane: A Pre- and Post-test Comparison of MBA Performance in Accelerated versus Traditional Core Microeconomics Classes by James H. Murphy Peer Reviewed James H. Murphy (jmurphy@westga.edu)

### HOW DO ONLINE STUDENTS DIFFER FROM LECTURE STUDENTS?

HOW DO ONLINE STUDENTS DIFFER FROM LECTURE STUDENTS? John Dutton College of Management North Carolina State University PO Box Dutton 7229 Raleigh, NC 27695-7229 Phone: 919-515-6948 Fax: 919-515-6943 Email:

### Determining Future Success of College Students

Determining Future Success of College Students PAUL OEHRLEIN I. Introduction The years that students spend in college are perhaps the most influential years on the rest of their lives. College students

### A COMPARISON OF COLLEGE AND HIGH SCHOOL STUDENTS IN AN ONLINE IT FOUNDATIONS COURSE

A COMPARISON OF COLLEGE AND HIGH SCHOOL STUDENTS IN AN ONLINE IT FOUNDATIONS COURSE Amy B. Woszczynski Kennesaw State University awoszczy@kennesaw.edu Debra Bass Geist Kennesaw State University dgeist1@students.kennesaw.edu

### Predicting Successful Completion of the Nursing Program: An Analysis of Prerequisites and Demographic Variables

Predicting Successful Completion of the Nursing Program: An Analysis of Prerequisites and Demographic Variables Introduction In the summer of 2002, a research study commissioned by the Center for Student

### Learning Orientations, Tactics, Group Desirability, and Success in Online Learning

Learning Orientations, Tactics, Group Desirability, and Success in Online Learning Diane D. Chapman, Ed.D. Teaching Assistant Professor North Carolina State University Since the inception of Web-based

### USING THE ETS MAJOR FIELD TEST IN BUSINESS TO COMPARE ONLINE AND CLASSROOM STUDENT LEARNING

USING THE ETS MAJOR FIELD TEST IN BUSINESS TO COMPARE ONLINE AND CLASSROOM STUDENT LEARNING Andrew Tiger, Southeastern Oklahoma State University, atiger@se.edu Jimmy Speers, Southeastern Oklahoma State

### The Effect of Tenure on Teacher Performance in Secondary Education

The Effect of Tenure on Teacher Performance in Secondary Education Elizabeth Phillips Policy Analysis and Management Honors Thesis Submitted May 2009 Advised by Professor Jordan Matsudaira Acknowledgements

### Analysis of the Effectiveness of Online Learning in a Graduate Engineering Math Course

The Journal of Interactive Online Learning Volume 1, Number 3, Winter 2003 www.ncolr.org ISSN: 1541-4914 Analysis of the Effectiveness of Online Learning in a Graduate Engineering Math Course Charles L.

### Where Class Size Really Matters: Class Size and Student Ratings of Instructor Effectiveness

Where Class Size Really Matters: Class Size and Student Ratings of Instructor Effectiveness Kelly Bedard and Peter Kuhn* Department of Economics University of California, Santa Barbara August 2005 Abstract

### Predicting the Performance of a First Year Graduate Student

Predicting the Performance of a First Year Graduate Student Luís Francisco Aguiar Universidade do Minho - NIPE Abstract In this paper, I analyse, statistically, if GRE scores are a good predictor of the

### MATH 140 HYBRID INTRODUCTORY STATISTICS COURSE SYLLABUS

MATH 140 HYBRID INTRODUCTORY STATISTICS COURSE SYLLABUS Instructor: Mark Schilling Email: mark.schilling@csun.edu (Note: If your CSUN email address is not one you use regularly, be sure to set up automatic

### Impact of Enrollment Timing on Performance: The Case of Students Studying the First Course in Accounting

Journal of Accounting, Finance and Economics Vol. 5. No. 1. September 2015. Pp. 1 9 Impact of Enrollment Timing on Performance: The Case of Students Studying the First Course in Accounting JEL Code: M41

### 2. Linear regression with multiple regressors

2. Linear regression with multiple regressors Aim of this section: Introduction of the multiple regression model OLS estimation in multiple regression Measures-of-fit in multiple regression Assumptions

### MULTIPLE REGRESSION AND ISSUES IN REGRESSION ANALYSIS

MULTIPLE REGRESSION AND ISSUES IN REGRESSION ANALYSIS MSR = Mean Regression Sum of Squares MSE = Mean Squared Error RSS = Regression Sum of Squares SSE = Sum of Squared Errors/Residuals α = Level of Significance

### STUDENT EVALUATION OF INSTRUCTIONAL EFFECTIVENESS OF WEB-BASED LEARNING STRATEGIES

STUDENT EVALUATION OF INSTRUCTIONAL EFFECTIVENESS OF WEB-BASED LEARNING STRATEGIES Dr. Lissa F. Pollacia, Northwestern State University, pollacia@nsula.edu Dr. Claude Simpson, Texas A & M University at

### LAGUARDIA COMMUNITY COLLEGE CITY UNIVERSITY OF NEW YORK DEPARTMENT OF MATHEMATICS, ENGINEERING, AND COMPUTER SCIENCE

LAGUARDIA COMMUNITY COLLEGE CITY UNIVERSITY OF NEW YORK DEPARTMENT OF MATHEMATICS, ENGINEERING, AND COMPUTER SCIENCE MAT 119 STATISTICS AND ELEMENTARY ALGEBRA 5 Lecture Hours, 2 Lab Hours, 3 Credits Pre-

### Regression Analysis (Spring, 2000)

Regression Analysis (Spring, 2000) By Wonjae Purposes: a. Explaining the relationship between Y and X variables with a model (Explain a variable Y in terms of Xs) b. Estimating and testing the intensity

### Chapter 9 Assessing Studies Based on Multiple Regression

Chapter 9 Assessing Studies Based on Multiple Regression Solutions to Empirical Exercises 1. Age 0.439** (0.030) Age 2 Data from 2004 (1) (2) (3) (4) (5) (6) (7) (8) Dependent Variable AHE ln(ahe) ln(ahe)

### Switching Economics Courses from Online Back to the Classroom: Student Performance and Outcomes

International Journal of Business and Social Science Vol. 2 No. 22; December 2011 Switching Economics Courses from Online Back to the Classroom: Student Performance and Outcomes Richard Vogel Department

### Web-based versus classroom-based instruction: an empirical comparison of student performance

Web-based versus classroom-based instruction: an empirical comparison of student performance ABSTRACT Evelyn H. Thrasher Western Kentucky University Phillip D. Coleman Western Kentucky University J. Kirk

### AN INVESTIGATION OF THE DEMAND FACTORS FOR ONLINE ACCOUNTING COURSES

AN INVESTIGATION OF THE DEMAND FACTORS FOR ONLINE ACCOUNTING COURSES Otto Chang, Department of Accounting and Finance, California State University at San Bernardino 5500 University Parkway, San Bernardino,

### RARITAN VALLEY COMMUNITY COLLEGE ACADEMIC COURSE OUTLINE MATH 111H STATISTICS II HONORS

RARITAN VALLEY COMMUNITY COLLEGE ACADEMIC COURSE OUTLINE MATH 111H STATISTICS II HONORS I. Basic Course Information A. Course Number and Title: MATH 111H Statistics II Honors B. New or Modified Course:

### Fundamentals of Economics Courses: Fun Course or a Positive Learning Experience?

Fundamentals of Economics Courses: Fun Course or a Positive Learning Experience? Timothy J. Schibik, University of Southern Indiana Daniel Friesner, Weber State University Mohammed Khayum, University of

### Knowledge Management & E-Learning

Knowledge Management & E-Learning, Vol.5, No.3. Sep 2013 Knowledge Management & E-Learning ISSN 2073-7904 A brief examination of predictors of e-learning success for novice and expert learners Emily Stark

### COMPARING STUDENT PERFORMANCE: ONLINE VERSUS BLENDED VERSUS FACE-TO-FACE

COMPARING STUDENT PERFORMANCE: ONLINE VERSUS BLENDED VERSUS FACE-TO-FACE David K. Larson University of Illinois at Springfield Department of Management Information Systems College of Business and Management

### Timothy M. Diette, Washington and Lee University George W. Kester, Washington and Lee University ABSTRACT

Student Course Evaluations: Key Determinants of Teaching Effectiveness Ratings in Accounting, Business and Economics Courses at a Small Private Liberal Arts College Timothy M. Diette, Washington and Lee

### The Effect of Admissions Test Preparation: Evidence from NELS:88

The Effect of Admissions Test Preparation: Evidence from NELS:88 Introduction For students planning to apply to a four year college, scores on standardized admissions tests--the SAT I or ACT--take on a

### The Influence of a Summer Bridge Program on College Adjustment and Success: The Importance of Early Intervention and Creating a Sense of Community

The Influence of a Summer Bridge Program on College Adjustment and Success: The Importance of Early Intervention and Creating a Sense of Community Michele J. Hansen, Ph.D., Director of Assessment, University

### Introduction. The busy lives that people lead today have caused a demand for a more convenient method to

On-Line Courses: A Comparison of Two Vastly Different Experiences by Sharon Testone, Ph.D. Introduction The busy lives that people lead today have caused a demand for a more convenient method to gain a

### Nursing Scholarship Program High School Seniors & College Nursing Program Applicants

ALSO AVAILABLE ONLINE HTTP://WWW.HNEF.ORG Nursing Scholarship Program High School Seniors & College Nursing Program Applicants Thank you for your interest in the Healthcare and Nursing Nursing Scholarship

### NCSS Statistical Software Principal Components Regression. In ordinary least squares, the regression coefficients are estimated using the formula ( )

Chapter 340 Principal Components Regression Introduction is a technique for analyzing multiple regression data that suffer from multicollinearity. When multicollinearity occurs, least squares estimates

### Issues in Political Economy, Vol. 12, August 2003

STUDENT EFFICIENCY: A STUDY ON THE BEHAVIOR AND PRODUCTIVE EFFICIENCY OF COLLEGE STUDENTS AND THE DETERMINANTS OF GPA Rebecca Nelson, Mary Washington College 1 The importance of a college education in

### Nursing Scholarship Program High School Seniors & College Nursing Program Applicants

ALSO AVAILABLE ONLINE www.hnef.org Nursing Scholarship Program High School Seniors & College Nursing Program Applicants Thank you for your interest in the Healthcare and Nursing Nursing Scholarship Program.

### Asynchronous Learning Networks and Student Outcomes: The Utility of Online Learning Components in Hyhrid Courses

Asynchronous Learning Networks and Student Outcomes: The Utility of Online Learning Components in Hyhrid Courses Daniel L. DeNeui and Tiffany L. Dodge The current research focuses on the impact that learning

### Revisiting Inter-Industry Wage Differentials and the Gender Wage Gap: An Identification Problem

DISCUSSION PAPER SERIES IZA DP No. 2427 Revisiting Inter-Industry Wage Differentials and the Gender Wage Gap: An Identification Problem Myeong-Su Yun November 2006 Forschungsinstitut zur Zukunft der Arbeit

### Office of Institutional Research & Planning

NECC Northern Essex Community College NECC College Math Tutoring Center Results Spring 2011 The College Math Tutoring Center at Northern Essex Community College opened its doors to students in the Spring

### Presented at the 2014 Celebration of Teaching, University of Missouri (MU), May 20-22, 2014

Summary Report: A Comparison of Student Success in Undergraduate Online Classes and Traditional Lecture Classes at the University of Missouri Presented at the 2014 Celebration of Teaching, University of

### Strategies for Teaching Undergraduate Accounting to Non-Accounting Majors

Strategies for Teaching Undergraduate Accounting to Non-Accounting Majors Mawdudur Rahman, Suffolk University Boston Phone: 617 573 8372 Email: mrahman@suffolk.edu Gail Sergenian, Suffolk University ABSTRACT: