Research Design & Statistics - Online

BIO 548 – 3 Credits
Cedar Crest College, Allentown, PA 18104, U.S.A.


Most of the fundamental ideas of science are essentially simple, and may, as a rule,
be expressed in a language comprehensible to everyone.”
— Albert Einstein

STATISTICS IS NO EXCEPTION.


Alan B. Hale, Ph.D., Professor of Biology
Office: Science Center 134
Email: abhale@cedarcrest.edu
Telephone: 610-606-4666 x3510
Website: www.cedarcrest.edu/abhale
Office Hours: weekly schedule or appt.; [Eastern Standard Time]

Experience: Dr. Hale began teaching statistics courses in 1981 and has 39 years of research experience involving statistical analyses.

A Welcome from Dr. Hale


Course Description: This online course has been designed for graduate students and professionals who are in the process of developing or actively participating in a research project and would like to enhance their statistical skills to effectively analyze and convey the information within their data set(s). The course not only presents a diversity of statistical and graphics techniques that will help participants address their current research needs, it also reveals new approaches one can use to answer subsequent research questions. Microsoft Excel and XLSTAT-Pro (www.xlstat.com) will be used to demonstrate a diversity of parametric, nonparametric, univariate, bivariate and multivariate statistical tests and tools. Demonstration of each tool/test will be presented within the context of an actual or hypothetical research project. Research Design & Statistics is 99% application and 1% theory; the goal being to rapidly and effectively help researchers use statistics in a correct and meaningful way. The course does not require previous training in statistics; however, active participation in the research process is essential for quality learning.

Platform & Duration:  Strictly Online – eCollege [access provided by Cedar Crest College; PC or Mac]; 8-week course

Registering for the Course:        Cedar Crest Students        Non-Cedar Crest Students
Please note: Given current policy, matriculated Cedar Crest students, i.e., those who are working toward a degree or certificate, are not permitted to audit BIO 548 or to take it on a pass/fail basis. Non-matriculated students and professionals, on the other hand, do have the option to take the course pass/fail, though students at other institutions are encouraged to check with their appropriate offices to be sure that P/F is acceptable. Given the design and learning philosophy associated with the course, auditing is not an option, and that the requirements for the course (see below) are the same for both modes of registration (grade or P/F).

Textbook:  None. Prepared background information on each statistical test/tool will be provided in electronic form within the course.  Additional online resources will be available either directly from the web or through the Cressman Library interface [http://library.cedarcrest.edu/index.shtm], which is accessible to all enrolled in the course. If anyone prefers to have one or more books to support their efforts in this course, Dr. Hale would gladly provide some recommendations.

Technology Requirements: Internet access; eCollege access (provided by Cedar Crest College when enrolled in course); Microsoft Office (at least Excel); XLSTAT-Pro [1-yr license (~$50/yr) or perpetual license (price varies, see www.xlstat.com/en/prices.html)]. As illustrated below, XLSTAT-Pro is well integrated into Microsoft Excel; this acts to streamline the process of data management and analysis. Although beyond the scope of this course, participants should know that many XLSTAT modules (e.g., 3-D visualization; dose effect analysis; survival analysis; statistical power; time series analysis) can be purchased separately to serve specific needs of the researcher. These modules work in conjunction with XLSTAT-Pro.



Course Objectives:
BIO 548 – Research Design & Statistics is designed to help participants:
•    enhance their ability to clearly define testable research questions.
•    design experiments that involve statistical analyses that have a high probability of yielding accurate and informative outcomes.
•    develop graphics and statistical skills that promote innovation and facilitate the analysis and sharing of experimental results with others.

Learning Outcomes:
Individuals who have successfully completed this course will have demonstrated the ability to:
•    effectively create and critique the design of a research project.
•    employ in a productive manner the tools and statistical tests available in Excel and XLSTAT-Pro to yield accurate and informative outcomes.

Course Content, Activities, and Assignments:
This online course was developed to help researchers find answers to their questions, i.e., extract more information from their data, and designed to maximize learning. Topics will be presented in a sequence that coincides with the development and execution of most research projects; keep in mind, however, that statistical analyses are not always linear, so regressions and digressions should be expected. In order to maximize the assimilation of these topics, the manner in which the statistical tests and tools are presented is crucial. Consequently, Dr. Hale reserves the right to make minor modifications to the content, activities, and assignments in this course in order to improve the quality of the experience for those currently involved. All changes, if any, will be added to the posted syllabus and conveyed to the current participants.

Week
Content
Activities/Assignments
Please note that the Assignment document (e.g, Week 1 Assignment) located on eCollege provides a much more clearly defined list of what is to be accomplished/submitted each week. Be sure to follow what is in the document when completing a weekly assignment; the material below is just an overview of the planned coverage.
1

(1) Introduction of instructor and course

(2) Effective use of tools within eCollege (threaded discussions; dropbox)

(3) Acquiring and installing XLSTAT-Pro

(4) Research foci and goals of participants

(5) Philosophy of science and the role of statistics

(6) Clearly defining research questions, and if appropriate, statistical hypotheses and tests



Read the Course Home Introduction

If you are not familiar with eCollege, review the material I included in the first Course Home announcement and then watch the Student Orientation Tutorial.

Carefully read the syllabus and ask for clarification, if necessary. Please note that a Research Statement is due on the last day of class; see Grading Criteria and Percent Distribution (below) for more information.

Begin contributing to the Participant Research Activities threaded discussion (item just below "Syllabus"); the intent is to introduce participants and to promote collaboration and feedback throughout the course. Participants should feel free to ask for feedback on the research design and statistics associated with their current research, or to offer suggestions on how others might modify their approach. This discussion will continue throughout the 8-week course. Associations may develop beyond the course and continue after its completion.

Begin posting questions, if they exist, on the FAQ threaded discussion; responses will help eliminate confusion on the part of one or more participants.

Purchase XLSTAT-Pro (annual student option or otherwise) (www.xlstat.com/en/prices.html) and install  on your computer; use XLSTAT online video tutorials
(www.xlstat.com/en/support/tutorials) to explain the process, if necessary.

Access and familiarize yourself with the availability of XLSTAT manuals (access code is provided with XLSTAT license):  www.xlstat.com/en/customers  At the top of the new window you'll see two tabs: Update and Manuals; the second will take you where you want to go.

Read and give a good bit of thought to the content of the following two documents: (1) Philosophy of Science and Statistics and (2) Importance of Research Question. If you clearly understand the content of these two documents you will avoid many hurdles down the road.

Review the weekly assignment; ask for clarification if necessary.

Complete and submit Week 1 assignment by next Monday at 12:00 noon (Eastern Standard Time).

2

Data Management Within Microsoft Excel
     Excel: Time-Saving Methods

Tools* - XLSTAT-Pro
     Data Flagging
     Min/Max Search
     Removing Text Values
     Exporting to GIF/JPG/PNG/TIF

Preparing Data - XLSTAT-Pro
     Data Sampling
     Distribution Sampling
     Variables Transformation
    

*Titles preceding "XLSTAT-Pro (e.g., Tools - XLSTAT-Pro) indicate the menu tab in which the subtitles (e.g., Data Flagging) reside.


Assignment from previous week (Week 1) due Monday by 12:00 noon (EST).

Review the Week 2 assignment; ask for clarification if necessary.

View materials illustrating the basics of data management within Excel. Recall that these materials are in the appropriate units within eCollege, in this case, within Week 2.

In general, each listed topic associated with XLSTAT-Pro has a separate document produced by the instructor that describes the tool/test, situations where it can be used, assumptions, if any, steps involved when employing the tool/test, and the interpretation of the output. Review these materials; request help if problems arise.

On occasion, downloadable sample Excel data sets will be available for participants to use, especially when they are without appropriate data for a particular tool/test. These data sets will have informative filenames and will be available in Doc Sharing (see Tools: at top of eCollege window). Open Doc Sharing to see what is available.

Continue to participate in the FAQ threaded discussion on problems faced while working with Excel, eCollege, XLSTAT-Pro or other aspects of the course. Participants should contribute questions, and also feedback to questions submitted by others if they have successfully conquered the noted hurdle. The professor will also be an active participant in this discussion. This interchange will become an ever-growing FAQ resource for current and future participants.

Continue to participate in the Participant Research Foci and Goals threaded discussion.

Complete and submit Week 2 assignment by next Monday at 12:00 noon (EST).

3

Visualizing Data - XLSTAT-Pro
     Scatterplots
     Parallel Coordinates Plots
     Error Bars
     Plotting a Function
     Adjusting Axes/Labels
     Orthonormal Plots
     Plotting Transformations
     Merging Plots

Describing Data - XLSTAT-Pro
     Descriptive Statistics and Univariate Plots
     Quantiles Estimation
     Histograms
     Normality Tests
     Resampling
     Similarity/Dissimilarity Matrices
     Descriptive Statistics for Contingency Tables


Assignment from previous week due Monday by 12:00 noon. (EST).

Review the Week 3 assignment; ask for clarification if necessary.

Review supporting materials as with Week 2, but for new topics. Again, never hesitate to ask for help if confusion arises. The FAQ threaded discussion is a good destination for your request. Otherwise, email Dr. Hale (abhale@cedarcrest.edu).

Continue to contribute to the two threaded discussions: (1) FAQ and (2) Participant Research Foci and Goals.

Complete and submit Week 3 assignment by next Monday at 12:00 noon (EST).
4

Parametric Tests - XLSTAT-Pro
     One-Sample t and z Tests
     Two-Sample t and z Tests
     Two-Sample Comparison of Variances
     k-Sample Comparison of Variances
     Multidimensional Tests (e.g., Mahalanobis)
     z-Test for One Proportion
     z-Test for Two Proportions
     Comparison of k Proportions
     Multinomial Goodness of Fit Test


Assignment from previous week due Monday by 12:00 noon. (EST).

Review the Week 4 assignment; ask for clarification if necessary.

Review supporting materials as with previous week, but for new topics.

Continue to contribute to the two threaded discussions: (1) FAQ and (2) Participant Research Foci and Goals.

Complete and submit Week 4 assignment by next Monday at 12:00 noon (EST).
5

Nonparametric Tests - XLSTAT-Pro
     Comparison of Two Distributions
          (e.g., Kolmogorov-Smirnov)
     Comparison of Two Samples
          (e.g., Mann-Whitney)
     Comparison of k Samples
          (e.g., Kruskal-Wallis)
     Cochran's Q Test
     McNemar's Test
     Cochran-Mantel-Haenszel Test
     One-Sample Runs Test


Assignment from previous week due Monday by 12:00 noon. (EST).

Review the Week 5 assignment; ask for clarification if necessary.

Review supporting materials as with previous week, but for new topics.

Continue to contribute to the two threaded discussions: (1) FAQ and (2) Participant Research Foci and Goals.

Complete and submit Week 5 assignment by next Monday at 12:00 noon (EST).
6

Modeling Data - XLSTAT-Pro
     Distribution Fitting and Statistical Testing
     Linear Regression
     Nonlinear Regression
     Logistic Regression
     Nonparametric Regression
    

Assignment from previous week due Monday by 12:00 noon. (EST).

Review the Week 6 assignment; ask for clarification if necessary.

Review supporting materials as with previous week, but for new topics.

Continue to contribute to the two threaded discussions: (1) FAQ and (2) Participant Research Foci and Goals.

Complete and submit Week 6 assignment by next Monday at 12:00 noon (EST).

7

Modeling Data - XLSTAT-Pro
     ANOVA
     ANCOVA
   
Correlation/Association Tests - XLSTAT-Pro
     Correlation Tests
     Tests on Contingency Tables
     Cochran-Armitage Trend Test

Analyzing Data - XLSTAT-Pro
     Factor Analysis


Assignment from previous week due Monday by 12:00 noon. (EST).

Review the Week 7 assignment; ask for clarification if necessary.

Review supporting materials as with previous week, but for new topics.

Continue to contribute to the two threaded discussions: (1) FAQ and (2) Participant Research Foci and Goals.

Complete and submit Week 7 assignment by next Monday at 12:00 noon (EST).

8

Analyzing Data - XLSTAT-Pro
     Principal Component Analysis (PCA)
     Discriminant Analysis (DA)

Course Wrap Up







Assignment from previous week due Monday by 12:00 noon. (EST).

Review the Week 8 assignment; ask for clarification if necessary.

Review supporting materials as with previous week, but for new topics.

Continue to contribute to the two threaded discussions: (1) FAQ and (2) Participant Research Foci and Goals.

Complete and submit Week 8 assignment by 5:00 p.m. (EST) on the last day of class.

Submit your Research Statement, i.e., the document that illustrates the design of your current/future research project, as described below in Grading Criteria. Recall that detailed guidelines for this statement are available in Week 8 within eCollege. Due: 5:00 p.m. (EST) on the last day of class.

Best wishes, and never hesitate to stay in touch!

                        
Disability Accommodations:
Students with disabilities who believe they will need accommodations for this class are responsible for contacting Academic Services (advising@cedarcrest.edu, CUR 109, 610-606-4666 ext. 4628) to provide documentation in support of a disability in accordance with that department's guidelines, copies of which can be located on MyCedarCrest (login information will be available when enrolled in course). To avoid any delay in the implementation of accommodations, students should contact Academic Services as soon as possible. Accommodations are not retroactive and cannot be provided until an accommodation letter or notification from Academic Services has been received by the faculty member. Any student registered with Academic Services should contact Dr. Hale as soon as possible for assistance in developing a plan to address your academic needs in this course.  Your cooperation is appreciated.

Honor Code and Academic Standards of Integrity:
Students enrolled in BIO 548 are expected to abide by the Cedar Crest College Honor Code and the Academic Standards of Integrity, as described in the graduate catalog. Details are provided at:
http://www.cedarcrest.edu/ca/catalog2011_2012/graduate/integrity_property.shtm#integrity

Grading Criteria and Percent Distribution:

    Threaded Discussion - FAQ: Courses and course materials are never perfect, there is always room for improvement. The Frequently Asked Questions (FAQ) threaded discussion should fill voids where voids exist, and also help current and future participants understand a topic more fully. If a question comes to mind, there is a good chance that the answer would be helpful to others as well. Please submit questions as they emerge,
and also feedback to questions submitted by others if you have successfully conquered the noted hurdle.

    Threaded Discussion - Research Foci & Goals:
The intent of the threaded discussion on the research foci and goals of the participants is to introduce participants and to promote collaboration and feedback throughout the course. Participants should feel free to ask for feedback on the research design and statistics associated with their current research, or to offer suggestions on how others might modify their approach. This is an opportunity to learn from others and to provide a helping hand if the participant is in the position to do so.

    Assignments: The key to learning statistics is to actually use each tool rather than just learning about it. Learning is further accentuated by using the tool with one's own data; linking the tool with one's data not only links the unknown with the known, which is important in learning, it also tends to open up more possibilities within one's research program. Obviously, one data set will not match all statistical tools; consequently, for these assignments, hypothetical or literature-derived data related to the participant's research program may be used. At times, sample data sets will be available in Doc Sharing (eCollege). Each week there will be an assignment that illustrates each participant's grasp of the concepts/tools/tests addressed that week. The details of the assignment will be posted on the Monday of that week during which the concepts, etc. are addressed; the completed assignment is due the following Monday, unless otherwise noted. Assignments are submitted as text documents (e.g., Word), unless another format is requested.

    Research Statement: A document that clearly conveys the design of your updated,* current research project or of an upcoming project. This should include research question(s), statistical hypotheses, statistical sampling approach, sample size, planned statistical analyses, and your anticipated concluding statement (to confirm proper match between sample and statistical population). Please Note: This document is seen solely by the instructor and will remain confidential, i.e., the research ideas will neither be used nor distributed to others by the instructor. The Research Statement is due the last day of class. *Influenced, in part, by the content of BIO 548.

ACTIVITY
GRADING CRITERIA
GRADING %
Threaded Discussions
          Research Foci & Goals:
          FAQ:
continued participation; quality of entries (and feedback, if any)

5%
5%
Statistical Tool/Test Assignments
(Details of each assignment will be
provided at the start of each week.)
criteria depend upon specific assignment, but in general, they include:
accurate statement of testable research question and hypotheses;
proper usage/analysis of tool/test; correct interpretation of outcome;
quality of written presentation

75%
[Week 1: 5%;
Weeks 2-8: 10% each]
Research Statement
clarity of research statement; quality of research design; choice of effective statistical tools/tests
15%
 

Grade Conversion:

Conversion of Numerical Grades (%) to Letter Grades
A
93-100%
A-
90-92.9%
B+
87-89.9%
B
83-86.9%
B-
80-82.9%
C+
77-79.9%
C
73-76.9%
C-
70-72.9%
D+
67-69.9%
D
60-66.9%
F
< 60%
Pass/Fail: A grade of C or better is required for a passing grade in this graduate course.
Grades will remain confidential and updated on eCollege throughout the 8-week session.