EDL 7150 Inferential Statistics Syllabus

EDL 7150
Inferential Statistics
Syllabus

Spring Term 2014
George H. Olson, Ph D, Instructor

Office: New College of Education, Room 212-H

Phone: 262-4963 (Office) 264-0442 (Home) 265-6994 (Cell)

Instructor's e-mail: olsongh@appstate.edu

Course e-mail (where to submit course work): olsongh2@gMail.com

Office Hours: Tuesdays, before class,
and by appointment

Class Meetings: See the Graphic of the Calendar.
A few sessions of this class will be conducted virtually.

COURSE DESCRIPTION

This is an intermediate course in inferential statistics. The focus of the course is on the use and interpretation of statistical procedures used with quantitative methods of research and evaluation. Topics covered include statistical analysis of measuring instruments (including procedures for evaluating the reliability and validity of tests and surveys), descriptive statistics, measures of variability and correlation, general linear models (including regression analysis, analysis of variance and covariance), logistic regression, and introductions to multilevel modeling, factor analysis, and structural equation modeling.

This course does not rely heavily on mathematical skills. Because I do not expect the students in the class to become statisticians, I do not expect them to possess the extensive mathematical foundations supporting the statistical procedures covered in the course. On the other hand an expectation of some mathematical prowess (say, at a level of 8th or 9th grade algebra) is not unreasonable. Nor will students be required to do much in the way of hand or calculator computation. Nowadays, computers handle the bulk of the work in statistical calculations.

The statistical analysis components of the Analysis ToolPak in Excel, SPSS, and other statistical software readily available on the web will be used in this course. SPSS is located on the University’s network server and is accessible via computers located in the RCOE computer labs and other computer labs throughout the campus. Additionally, doctoral students in this course are encouraged to obtain the Graduate Student Version of the package to load onto their personal computers.

Since this is an intermediate course in statistics, a basic understanding of elementary statistical concepts is assumed. If you are not current with these concepts you would be well advised to obtain a textbook in elementary or introductory statistics (two excellent sources are listed below)..

TEXTBOOKS and RESOURCE MATERIALS

Pedhazur, E. J. & Schmelkin, L. P. (1991). Measurement, Design, and Analysis: An Integrated Approach. Don't let the early publication date of this book concern you. Pedhazur and Schmelkin's text remains one of the most comprehensive, yet readable, texts on quantitative research and analysis available today. While this book can be pricey, you should be able, using Google, to find copies for around $50 or less (this is the only book you will have to buy for this course.)

Richard Lowry, PhD (undated). Concepts and Applications of Inferential Statistics. This is a free, full-length statistics book. Note, this book will serve as our primary textbook.

Richard Lowry, PhD (undated). VassarStats. This is a companion (to the previous) set of tools for performing a wide variety of statistical computations.

Rice Virtual lab in Statistics: HyperStat Online (An online statistics book with links to other statistics resources on the web).

M. K. Trochim (undated). Research Methods Knowledge Base (RMKB). This is another, free rich resource for design and analysis.

StatTrek, another free suite of statistical tutorials, tables, tools, calculators and online resources.

American Psychological Association (2009). Publication Manual of the American Psychological Association: Sixth Edition. Washington, DC: American Psychological Association.

Microsoft Excel: Many of the statistical procedures introduced in this class can be computed using Excel. If you do not have the Data Analysis ToolPac installed with your version of Excel, install it. Hear are the instructions for installing the Excel Data Analysis Tool Pack

You are encouraged, also, to obtain an intermediate-level textbook on statistics--particularly one with an educational, psychological, or behavioral sciences orientation. Two that I particularly like are:

Sprinthall, R. C. (2011) Basic Statistical Analysis (11th Ed.). Publisher: Pearson Higher Education. Earlier editions of this book are readily available by searching Google.

Howell D. C. (2007), Statistical Methods for Psychology (6th Ed.). Publisher: Thomson/Wadsworth. [This is a more advanced, intermediate text. We will use some of his examples in this course.]

Other available statistical procedures available, free, on the web.

OBJECTIVES OF THE COURSE

The objective of this course is to enable students to analyze and interpret data, collected from a variety of types of research designs, within a linear model framework. Specifically, at the conclusion of this course students should be able to do the following:

(1) Set up data, from a suitable quantitative study, for data analysis using Excel, SPSS, and other statistical software.
(2) Summarize a set of data using appropriate descriptive statistics.
(3) Use Analysis of Variance (ANOVA) or Analysis of Covariance (ANCOVA) where appropriate to analyze and interpret data collected from factorial designs.
(4) Use multiple linear regression (MLR) procedures to compute partial and semi-partial correlation analyses and interpret the results.

(5) Analyze and interpret data from a prediction study using one criterion variable and multiple predictor variables.

(6) Use regression analysis to analyze and interpret data collected from ANOVA and ANCOVA designs.

(7) Understand and interpret ANOVA, ANCOVA, and MLR results reported in published reports of research.

(8) Evaluate the reliability and validity of a measuring (or survey) instrument.

Additionally, as time allows...

(9) Set-up, compute, and interpret a factor analysis.

(10) Set-up, compute, and interpret a path analysis.

(11) Understand the motivation for using a multi-level design or structural equation modeling.

OBJECTIVES OF THE COURSE

(1) Set up data, from a suitable quantitative study, for data analysis using Excel, SPSS, and other statistical software.
(2) Summarize a set of data using appropriate descriptive statistics.
(3) Use Analysis of Variance (ANOVA) or Analysis of Covariance (ANCOVA) where appropriate to analyze and interpret data collected from factorial designs.
(4) Use the multiple linear regression (MLR) procedures to compute partial and semi-partial correlation analyses and interpret the results.

(5) Analyze and interpret data from a prediction study using one criterion variable and multiple predictor variables.

(6) Use regression analysis to analyze and interpret data collected from ANOVA and ANCOVA designs.

(7) Understand and interpret ANOVA, ANCOVA, and MLR results reported in published reports of research.

(8) Evaluate the reliability and validity of a measuring (or survey) instrument.

Additionally, as time allows...

(9) Set-up, compute, and interpret a factor analysis.

(10) Set-up, compute, and interpret a path analysis.

REQUIREMENTS OF THE COURSE

Tests

There will be three, take-home tests, The first of these tests is a basic statistics competency test and will be given at the end of the second week of class. A practice test is available. You are encouraged to take the practice test. If you do not obtain a satisfactory score on the basic statistics competency test you are not likely to fair well in this course.

The second test will be given half-way through the course and will assess your competence over all the material covered up to that point.

The third test is a final examination and is cumulative.

The first two tests will, together, count 30 percent toward your grade in the course. The Final Examination will count 60 percent toward your grade.

Each test is to be completed as a solo effort (you are NOT permitted to work in groups on this test.) However, practice tests that are similar to he actual tests will be available. You are permitted to work cooperatively on the practice test.

The conversion of numerical numerical points earned to letter grades will be as follows:

86-100 A 76-85 B 66-75 C

Note: The instructor reserves the option of changing the above requirements or class schedule as needed to fulfill the goals and objective of the course.