DPLS 722 Spring 2009 Quantitative Data Analysis
GONZAGA UNIVERSITY
Doctoral Program in
Leadership Studies
Syllabus for DPLS 722: Quantitative Data Analysis
Spring 2009
Professor: Sandra M. Wilson; wilson@gonzaga.edu (509-313-3517)
Hybrid Course Design:
(a) Online presentation for module content
(b) Face-to-face presentation of lab portion of the class
(Jan 31, Fe 28, March 21, April 4)
Tilford bldg room 107
Course Overview
Statistics are ways of understanding more about questions and issues that interest us. The Tao of Statistics is a journey down a path that leads to an intriguing view of the world. The statistical view of the world is of a place where knowledge is neither certain nor random. Statistical portraits are painted in pastel rather than in primary colors. . . . The Tao of Statistics lays a path to this understanding of the world. The path leads to a view of the subtle patterns in life that were invisible before. (Dana Keller, 2006, The Tao of Statistics, p. ix)
Quantitative data analyses require the use of statistics (descriptive and inferential) to summarize data collected, to make comparisons of data sets, and to generalize results obtained for a sample back to the population from which the sample was drawn. Statistics provide portraits of phenomena that help one to "see what was invisible before."
Strategic Goal: This course is designed to help students learn to think like "post-modern" research statisticians who are able to make reasonable and responsible judgments about data that enhance understanding of phenomena. Thinking like statisticians requires students to learn and employ frameworks for analyzing and interpreting patterns that exist within data sets and to communicate clearly to others the meaning of these patterns.
This course approaches statistics from a problem-solving perspective as emphasis is placed on selecting appropriate statistical techniques for various research designs and on interpreting and reporting data analyses results. Computer data analysis (using the windows 16.0 version of the Statistical Package for the Social Sciences (SPSS) will be a primary focus of the course to further illustrate the use and interpretation of statistics in research.
The Hybrid Approach
Blackboard will be used to present the online portion of the course. The course content is organized into four main modules, some of which are broken down into sub modules. The content of the modules, and sub modules, are designed to provide a foundation for understanding how statistics can be applied to help understand phenomena of interest to the researcher. The modules are organized as follows:
Module 1: Research Design and Hypothesis Testing
Module 1A: Overview of Statistics for Quantitative Research
Module 1B: Sampling Distributions and Inferential Parametric Statistics
Module 1C: An Introduction to Hypothesis Testing
Module 2: Research Designs for Measuring Group Differences
Module 2A: The t-test for a Single Sample Design
Module 2B: The t-test for Two Independent Samples
Module 2C: The t-test for Two Dependent or Related Samples
Module 2D: Hypothesis Testing for One-way and Two-way Design
Module 3: Research Designs for Determining Relationships and Prediction Models (Correlation and Regressions Analyses)
Module 4: Non Parametric Statistics for Determining Association (Chi-square)
The face-to-face portion of the course (4, four-hour sessions) will focus on application of content learned through the online portion of the course. More specifically, the face-to-face sessions will be a laboratory session that will allow you to analyze various data bases using SPSS in order to answer research questions of interest. As well this portion of the course will provide time for you to develop your final project for the course.
Because this is the first semester teaching the course as a hybrid (online and face-to-face), I realize there may need to be some adjustments along the way. Your feedback as to how this new course design is helping or impeding your learning would be greatly appreciated at any time during the semester. Please know I am willing to work with anyone over the phone, online, or face-to-face as needed. If you are feeling anxious about the content, please do not hesitate to contact me (earlier is better than later so you don't fall behind in the class). You can either call or email me.
I sincerely hope you enjoy the course.
Course Goals
Overall, this course is designed to enable students to learn how to:
- Formulate research questions and corresponding statistical hypotheses that can enhance understanding of a given phenomena
- Create or use existing databases to seek answers to research questions or to test hypotheses
- Select appropriate statistical techniques for a given question or hypothesis statement
- Apply statistical procedures to test hypotheses using SPSS
- Interpret SPSS computer printouts
- Communicate findings verbally and in written format
Note: Each module includes objectives specific to that module.
Course Evaluation
Grades for the course will be based on:
- Participation in online discussions (15%)
- Module Application Questions (15%)
- SPSS lab exercises (25%)
- Course "Final Application Exam" online (20%)
- Statistics project (25%)
Course Texts
Required:
Norusis, M.J. (2008). SPSS 16.0 guide to data analysis. Englewood Cliffs, NJ: Prentice Hall.
Module Packages designed by Sandra Wilson (presented on Blackboard)
Optional (but strongly recommended):
Hinkle, D., Wiersma, W., & Jurs, S. (any edition). Applied statistics for the behavioral sciences. Boston: Houghton Mifflin.
Course Calendar
Dates | Reading Assignments | Application Assignments | Online Discussion |
January 17-30 | Listen to course introductory video Read online postmodern research articles (see links posted on Blackboard assignments) Read Module 1(A, B, C) and corresponding reading assignments in SPSS and Hinkle et al texts | Complete application questions for Module 1 Your responses can be submitted on Blackboard anytime between Ja 20-30. OR, you can bring a hard copy to the lab class on Ja 31. | Discussion questions and guidelines for submitting your responses are posted on the Blackboard site. Your responses to Discussion # 1 are to be posted on the discussion board anytime between Ja 22 -28. |
January 31 (meet on campus) | Review Module 1 (A,B,C) | Review Module 1 application assignments In class Lab# 1 Application:
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February 1-27 | Read Module 2 (A,B,C) and corresponding reading assignments in SPSS and Hinkle et al texts | Complete SECTION I of the application questions for Module 2 Your responses can be submitted on Blackboard anytime between Fe 17-27; OR, you can bring a hard copy to the lab class on Fe 28. | Discussion questions and guidelines for submitting your responses are posted on the Blackboard site. Your responses to Discussion # 2 are to be posted on the discussion board anytime between Fe 14-20. |
February 28 (meet on campus)
| Review Module 2 (A,B,C) | Review Module 2 (Section I) application questions Outline for your FINAL STATS PROJECT due In class Lab# 2
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March 1-20 March 1-20 (cont.)
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Read Module 2 D and corresponding reading assignments for SPSS and Hinkle et al texts Read Module 3 and c corresponding reading assignments for SPSS and Hinkle et al texts
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Complete application questions for Module 2 (Section II) Complete application questions for Module 3 Your responses for both Module 2 (Section II) and for Module 3 can be submitted on Blackboard anytime between March 10-20. OR, you can bring a hard copy to the lab class on March 21.
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Discussion questions and guidelines for submitting your responses are posted on the Blackboard site. Your responses to Discussion # 3 are to be posted on the discussion board anytime between March 7-13. |
March 21 (meet on campus)
| Review Module 2D Review Module 3 | Review Module 2 (Section II) application questions In class Lab# 3
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April 4 (meet on campus)
| Read Module 4 and corresponding reading assignments in SPSS and Hinkle et al texts | Review Module 3 application questions Complete Module 4 application questions (submit between April 10-17) In class Lab# 4
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April 18 (final class date)
- 1. The Final Application Exam (submitted online)
- a. The exam will be posted on Blackboard on April 15. Your responses are to be submitted online by April 18.
- b. You may confer with other students in the class regarding your responses to the Final Application Exam questions prior to submission
- 2. Your statistics project is due in my office by April 25. You may need to mail your project to me given I will need to see your SPSS computer printouts.
- 3. Your SPSS lab exercises are due in my office by April 25 (your answers may be submitted on line or you can mail them to me).
- 4. Regarding revisions you have made in your responses to the Module Application Questions: you will need to resubmit these changes to me by April 25 (otherwise, I will grade what has been submitted prior)
1/28/09
