EDL 7150
Inferential Statistics
Syllabus

NOTE This course is not offered this term. What follows is the syllabus for spring 2010, the last time Dr. Olson offered the course

Spring Term 2010
George H. Olson, Ph D, Instructor

Office: Duncan Hall, Room 327-B

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: TBA

Class Meetings: TBA.
Several 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)..

TEXTBOOK

There is no formal statistics text for this class. However, we will use the following resources.

William M.K. Trochim, Research Methods Knowledge Base. The author provides the following description of this monumental work:

The Research Methods Knowledge Base is a comprehensive web-based textbook that addresses all of the topics in a typical introductory undergraduate or graduate course in social research methods.  It covers the entire research process including: formulating research questions; sampling (probability and nonprobability); measurement (surveys, scaling, qualitative, unobtrusive); research design (experimental and quasi-experimental); data analysis; and, writing the research paper.  It also addresses the major theoretical and philosophical underpinnings of research including: the idea of validity in research; reliability of measures; and ethics.  The Knowledge Base was designed to be different from the many typical commercially-available research methods texts.  It uses an informal, conversational style to engage both the newcomer and the more experienced student of research.  It is a fully hyperlinked text that can be integrated easily into an existing course structure or used as a sourcebook for the experienced researcher who simply wants to browse.

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. (Any recent edition). Basic Statistical Analysis.. Publisher: Allyn and Bacon [This is an excellent introductory text)

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.

Additional readings, all of which are available in the "Directory of Journal Articles" will also be required.

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 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.

(11) Set-up, compute, and interpret a multilevel model analysis.

(12) Set-up, compute, and interpret a structural equation model analysis.

REQUIREMENTS OF THE COURSE

Tests

There will be several formative, take-home tests, These tests, which, for the most part, are based on weekly homework assignments will be used mainly for assessment for learning. As a group, these weekly tests will count ten percent toward your grade in this course. Additionally, there will be three formal tests: Each of these formal tests will be comprehensive. In other words, each will include material from earlier in the course. The first two of the formal tests will, together, count 30 percent toward your grade in the course. The Final Examination will count 60 percent toward your grade.

The conversion of numerical grades 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.