EDUR 8131 Spring 2011 Instructor: Bryan W. Griffin (bwgriffin@GeorgiaSouthern.edu) 
Announcements 
Updated ANCOVA notes highlighted in yellow.
PDF Files
Creating PDF files:
Here are a few free web page that convert files to PDF over the internet:
I use the following free software to create my PDF files (it leaves no watermark): http://www.primopdf.com/
I also use OpenOffice to create some free PDF files. Open Office is a free Office Suite similar to Microsoft Office (Open Office leaves no watermark): http://www.openoffice.org/
If you want further tips and links for converting to free PDFs, read this site http://www.pruittfamily.com/paul/freepdf.htm or this one http://www.masternewmedia.org/2002/03/31/creating_pdfs_without_adobe_acrobat_part_ii.htm
Course Index (e.g., tests, activities, reading and other material to review for each class session)
 One and Two Samples ttest (answers)
 Correlated Samples ttest (answers)
 Correlation (answers)
 Chisquare (with answers)
 ANOVA (answers note this is a Word Document)
 Regression (see regression notes)
 ANCOVA (to be added)
 Notes 1 Descriptive Statistics
Excel file: 1. SD, Variance, and Z scores Notes 2 Normal Distribution and Standard Scores
 Notes 3 Statistical Inference
Excel file: 2. Population, Sample, and Sampling Distributions Notes 4 Hypothesis Testing and One Sample Z Test
Excel file: 3. Coin Flip Notes 5 ttests
Excel files:
4. One Sample ttest,
5. Two Sample ttest,
6. Correlated Sample ttest ;
Critical tvalues table:
ttables.pdf Notes 6 Correlation
Excel files:
7. Correlation Notes 7 Chisquare
Excel files:
8. Goodness of fit chisquare,
9. Association chisquare Notes 8a Simple Regression (read also Regression with one quantitative IV )
 Notes 8b Multiple Regression (read also Regression with two quantitative IVs )
 Notes 8 ANOVA
Multiple Comparisons in Excel: Bonferroni and Scheffe
Multiple Comparisons in Zoho (online spreadsheet): Bonferroni and Scheffe (this spreadsheet does not work correctly) Notes 9d ANCOVA
Sample Data
 Supplemental Reading: Stevens Chapter 7 ANCOVA
 Excel Spreadsheet for Interactions
 Video Tutorial: Oneway ANCOVA with three groups
 Video Tutorial: Twoway ANCOVA
 Video Tutorial: Oneway ANCOVA with Factor*Covariate Interaction (Unfortunately sound spikes and breaks occasionally)
 Sample Data 1: Fictional salary discrimination
 Sample Data 2: Gun control and homicides by state
 Sample Data 3: Fictional achievement data  homework with parental support
 Sample Data 4: Fictional data showing ANCOVA power vs ANOVA
 Sample Data 5: Car MPG by country of origin controlling for horsepower and weight
 Add Waldron data to illustrate difference between gain score and ANCOVA
Topic 
Moore & McCabe 5th ed. 
Moore, McCabe, & Craig 6th ed. 
Moore, McCabe, & Craig 7th ed. 
1.
Measurement (scales, variables) 
Chapter 1  Chapter 1  Chapter 1 
2.
Hypotheses 
Pages 402403 
Pages 374376 
Pages

3.
Overview of Descriptive and Inferential Statistics 
Chapter 3 (sampling)  Chapter 3 (sampling)  Chapter 3 (sampling) 
4.
Displaying Data with Graphs 
Chapters
1,
2 
Chapters
1,
2 
Chapters
1,
2 
5.
Percentile Ranks 
Chapter

Chapter

Chapter

6.
Central Tendency 
Chapter 1  Chapter 1  Chapter 1 
7.
Variability 
Chapter

Chapter

Chapter

8.
Standard Scores 
Chapter

Chapter

Chapter

9.
Normal Curve and Probability 
Chapter 1  Chapter 1  Chapter 1 
10.
Hypothesis Testing 
Chapter 5, 6  Chapter 5, 6  Chapter 5, 6 
11.
One sample ztest 
Chapter 6  Chapter 6  Chapter 6 
12.
ttest (onesample, independent samples, correlated) 
Chapter 7  Chapter 7  Chapter 7 
13.
Correlation (Pearson r) 
Chapter 2, 10  Chapter 2, 10  Chapter 2, 10 
14.
Chisquare (c^{2}) (test for
association) 
Chapter 9  Chapter 9  Chapter 9 
15. Regression 
Chapter 2, 10, 11  Chapter 2, 10, 11  Chapter 2, 10, 11 
16.
ANOVA 
Chapter 12  Chapter 12  Chapter 12 
17. ANCOVA (time permitting) 
 
 
 
Course Calendar (will be revised throughout term)
Session 1 (1/18): 5pm to 7:45pm
 Syllabus
 Begin Notes 1
 Variables and scales of measurement (variable/constant; scales; quan./qual.; IV/DV) (practice exercise)
 Hypotheses (directional/nondirectional/null; qual. vs. quan. wording; categories compared; writing; problematicno difference between IV and DV, qual. IV affects DV [e.g., type of instruction affects DV]) (practice exercise #1, practice exercise #2)
 Displaying Data (frequency distributions, stemandleaf, bar charts, histograms, pie charts, box plots, scatterplots; practice exercise for displaying data)
 Overview of things to come; read on your own  Descriptive Statistics and Graphical Displays (correlation coefficients and scatterplots) and Inferential Statistics (practice exercise)
Session 2 (1/25)
 Resume discussion from Session 1 (spr 2011: resume at scatterplots; fall 09, covered through displaying data)
 Central tendency (mode, median, mean)
 Variability (range, variance, standard deviation)
 Homework activity for material covered above (variability, central tendency, graphical displays), do on your own:
tests/edur_8131_homework_central_tendency_variability_graphics.pdf Begin Notes 2
 Normal curve and skew
 Percentiles and percentile rank
 Standard scores  z score, T score
 Probability and finding area under standard normal curve (Excel table with area to left of Z: Z Table); below is supplemental reading on calculating area under normal curve: http://wwwstat.stanford.edu/~naras/jsm/NormalDensity/NormalDensity.html
 Homework activity for z scores:
 Supplemental reading materials on topics covered above in case you find the course notes or textbook is unclear.
 http://davidmlane.com/hyperstat/index.html
 http://www2.sjsu.edu/faculty/gerstman/StatPrimer/
 http://espse.ed.psu.edu/statistics/Chapters/contents1.html
 http://statwww.berkeley.edu/users/stark/SticiGui/Text/
 http://www.anu.edu.au/nceph/surfstat/surfstathome/surfstat.html (select "Detailed Content" to see what's available)
Additional readings and useful links follow.
Session 3 (2/1)
 Review Notes 2 (fall 09, cover conversion z to raw, find twotailed .05 and .01 z scores)
 Begin Notes 3
 Hypothesis testing:
 Statistical Inference, Hypothesis Testing (read this: logic of hypothesis testing)
 Central Limit Theorem Illustrated
 Excel file showing 95% CI and Standard Error of the Mean: http://www.bwgriffin.com/gsu/courses/edur8131/content/Example_Calculating_SE_of_Mean_adv.xls
 Some additional readings on the logic of hypothesis testing:
Session 4 (2/8)
 Resume Notes 3 (note, fall 09 spring 10 session 3 ended at Notes 3.8 confidence intervals)
 Confidence Intervals
 Excel file showing 95% CI and Standard Error of the Mean: http://www.bwgriffin.com/gsu/courses/edur8131/content/Example_Calculating_SE_of_Mean_adv.xls
 Properties of Estimators
 Begin Notes 4 (Hypothesis Testing and Onesample Z test):
 One Sample ztest (two tailed vs. one tail tests and probability) (Instructor's note: partially covered this, did not get to material below)
 Hypothesis testing  power, type 1 and type 2 errors, pvalues
 One sample ttest; maybe start twoindependent samples ttest (seldom are ttests covered during session 5).
 Some readings on ttest can be found here:
 http://www2.chass.ncsu.edu/garson/pa765/ttest.htm
 http://www2.sjsu.edu/faculty/gerstman/StatPrimer/Hyptest.PDF
 also check online statistics books listed in Session 1 above
 Homework activity for z scores and z test:
Session 5 (2/15)
 Resume Notes 4 (fall 09 and spring 10, finished one sample z test notes 4.2 session 4; begin at 4.3):
 Notes 4.3: Short Cut to Pvalues
 Hypothesis testing  power, type 1 and type 2 errors, pvalues
 Some additional readings on the logic of hypothesis testing:
 Answer Questions about Test 1 (assuming we complete Notes 4 this chat session)
 Begin Notes 5: ttests  covered onesample ttest
Test 1 posted sometime after Session 5 (assuming Notes 4 is completed, otherwise Test 1 posted after Session 6)
Session 6 (2/22)
 Continue Notes 5 (spring 10 covered one and two group ttest; fall 09  covered one sample ttest, resume at two group ttest):
 One Sample ttest
 Confidence Intervals About Sample Means
 Two Independent Samples ttest
 Confidence Intervals About Mean Difference (cont. two independent samples ttest)
 Two Correlated Samples ttest
 CI with correlated samples ttest (same formula as above)
 Some readings on ttest can be found here:
 http://www2.chass.ncsu.edu/garson/pa765/ttest.htm
 http://www2.sjsu.edu/faculty/gerstman/StatPrimer/Hyptest.PDF
 http://www2.sjsu.edu/faculty/gerstman/StatPrimer/independ.pdf
 http://espse.ed.psu.edu/statistics/Chapters/Chapter10/Chap10.html
 http://www2.sjsu.edu/faculty/gerstman/StatPrimer/paired.pdf
 http://espse.ed.psu.edu/statistics/Chapters/Chapter10/Chap10.html
 One sample, two independent sample, and correlated samples ttests exercises with answers:
http://coe.georgiasouthern.edu/foundations/bwgriffin/edur8131/edur_8131_homework_t_tests.pdf
 See also Exercises in Course Index above for more on ttests
Session 7 (3/1)
1. Finished correlated samples ttest (spring 10; began at correlated ttest)
2. Began Notes 6, Correlation (useful information on reviewing scatterplots: correlation coefficients and scatterplots ).
3. Supplemental correlation notes below:
 https://webct.ucf.edu/dav/psy3214a/reach/notes/notes4correlation.html
 http://www.wadsworth.com/psychology_d/special_features/ext/workshops/correlation.html
 http://www2.chass.ncsu.edu/garson/pa765/correl.htm
 http://davidmlane.com/hyperstat/A34739.html
 http://www.wellesley.edu/Psychology/Psych205/pearson.html
 http://www.une.edu.au/WebStat/unit_materials/c6_common_statistical_tests/test_signif_pearson.html
4. Begin Notes 7 (chisquare)
5. Some readings on chisquare can be found here:
Session 8 (3/8)
Spring 2011  unable to enter chat session; chat canceled.
1. Continue Notes 6 (spring 10 resume at 6.8, correlation matrices, illustrate correlations in spss/excel; fall 09: covered correlation, need now to illustrate finding r in Minitab/Excel and reporting results in APA style)
2. Begin Notes 7 Chisquare (fall 09 covered goodness of it)
3. Some readings on chisquare can be found here:
Test 2 posted sometime after Session 8 (assuming coverage of chisquare is completed, otherwise Test 2 posted after Session 9)
Spring Break (3/15)
Session 9 (3/22)
 Begin (and Finish) Notes 7, Chisquare, if needed (fall09  covered test of association)
 Begin Notes 8a Simple Regression (fall 09  ended at finding residuals for ratings data)
Session 10 (3/29)
Resume Notes 8a Simple Regression (fall 09  resume with finding residuals for rating data, covered through model inference  reviewed with several examples of literal interpretation of coefficients; end at coefficient inference)
Session 11 (4/5)
 Continue with simple regression (f 09  resume this chat with coefficient interpretation in simple regression, ended at ice cream data)
 Begin multiple regression (end at ice cream example)
Session 12 (4/12)
 Continue with multiple regression (fall 09  begin ice cream data  show predicted values, residuals and R, R^2)
 Begin Oneway ANOVA
Session 13 (4/19)
 Resume ANOVA
 Begin Multiple Comparison Procedures under ANOVA (called Post Hoc) (fall 09, illustrated logic of Bonferroni correction, demonstrated comparisons in Zoho)
Session 14 (4/26)
 Address any remaining issues on ANOVA or multiple comparisons (s10, began ANCOVA; f 09 resume Zoho, and presenting results in APA style)
 ANCOVA
Session 15 (5/3)
 Finish ANCOVA
 Q&A about Test 3
Test 3 responses due (5/10)
NOTE  Material below this point is not yet organized into sessions
Course Assessment Questionnaire
General Readings on ANOVA:
ANCOVA
Note to self  add links to online statistical programs, e.g.
http://home.ubalt.edu/ntsbarsh/Businessstat/otherapplets/SampleSize.htm#rmenu
http://noppa5.pc.helsinki.fi/koe/flash/flash.html
Office Information
Hours
By chance or appointment. Best to contact me via email to arrange an appointment.
Telephone Numbers
Office (Room 2128 College of Education Building): 9124780488
Department of Curriculum, Foundations, and Research: 9124785091Use GeorgiaView to contact me. If GeorgiaView is not working, my regular email address is bwgriffin@GeorgiaSouthern.edu, but please use GeorgiaView for courserelated communications.
Department of Curriculum, Foundations, and Reading
P.O. Box 8144
College of Education
Georgia Southern University
Statesboro, GA 30460
Course Description
This course is will provide an introduction to statistics, both descriptive
and inferential, and the application of statistics to educational research.
Topics covered range from simple descriptive statistics, such as mean and
variance, to inferential methods, such as ttests, chisquare tests of
association, analysis of variance, and analysis of covariance.
Texts
Required  Moore, D. & McCabe, G. (2006, 2009, 2012). Introduction to the practice of statistics (5th, 6th, or 6h ed. acceptable). New York: Freeman.
Note that 5th and 6th editions may be found online for less than $20. Try searching for ISBN 0716764008 on google.com shopping, www.amazon.com, or www.alibris.com, for example.
Web Pages
http://www.bwgriffin.com/gsu/courses/edur8131/
Software (Recommended)
SPSS (PASW) Version 10.0 or higher. Version 18 of the Graduate Pack Base can be rented for 6 months for $35 here:
Other student options and pricing for SPSS/PASW can be found here:
http://www.spss.com/vertical_markets/education/online.htm
Course Activities
To facilitate learning of statistical analysis of data and reporting of
statistical results, numerous computer replications of examples from readings
and outofclass exercises will be provided.
Content Covered
Examinations
There will be three tests administered during the term. Each test will focus
on conceptual components of statistical analysis, computer applications, choice
of statistical procedures, and written results and interpretations.
Grading
Each test will be weighted equally at 1/3 of the final grade. Final grades
will be assigned based on the following table:

90
and above 
=
A 


80
to less than 89.999 
=
B 


70
to less than 79.999 
=
C 


60
to less than 69.999 
=
D 


59.999
and below 
=
F 

You will be allowed to take any missed test for any absence (no excuse is
necessary). Should you not provide responses to a missed test before the end of
the term, an I (incomplete) will be assigned as your final course grade and
will remain until all missed tests are completed, or for one year and then
become an F.
If you fail to take the final test on the scheduled date, you may take it
during a time that is convenient for the instructor. Tests cannot be taken
early.
Attendance
You may come and go as you please.
Withdrawing from Class
The university sets a specific date in which you may withdraw from a course without an academic penalty. In this course, however, you may withdraw without an academic penalty (i.e., you will received a WP) until the last day of regular class (this excludes exam week), no questions asked, no matter what your current performance. My policy of assigning WPs is contingent upon the approval of the CFR department chair and COE Dean (i.e., a WP is not guaranteed).
To withdraw after the drop date, contact the registrar's office to learn what form is needed (it may be called "petition to withdraw" or something similar). Complete that form and submit to me so I may sign and forward to my departmental chair. It may also be possible to withdraw via emailagain, contact the registrar's office to learn if possible and how.
Academic Integrity Expectations
Students are expected to abide by the GSU student conduct code and
regulations regarding academic integrity. Academic misconduct such as cheating
and plagiarism will be reported to the Office of Judicial Affairs and
appropriate penalties imposed, such as a grade of zero on the targeted
activity. See information on student
conduct in the relevant student handbook for details.
Disability Accommodations
If a student has a documented and declared disability, reasonable
accommodations will be provided if requested by the student according to the
recommendations of the GSU Disabled Student Services office.
How This Course Supports the Colleges Conceptual Framework
The College of Educations conceptual framework advances the theme of reflective educators for diverse learners. In this course information will be learned that should make each student a more knowledgeable consumer of educational research. With this knowledge you will be better able to evaluate critically current and recommended practices when analyzed empirically.
Types of Statistical Procedures and Their Characteristics
Statistical
Test 
Independent Variable 
Dependent Variable 
Special Feature 
Example Hypothesis 
(1) Pearson's r (correlation coefficient) 
Quantitative 
Quantitative 

There is a positive relationship between intelligence and mathematics
achievement scores. 
(2) ttest for independent groups 
Qualitative 
Quantitative 
IV has only 2 categories 
There will be a difference between boys and girls on mathematics
achievement scores. 
(3) ChiSquare c2 
Qualitative 
Qualitative 
Both IV and DV may have more than two categories 
Males will be more likely to drop out of school than females. 
(4) Oneway ANOVA (Analysis of Variance) 
Qualitative 
Quantitative 
IV may have 2 or more categories. 
There will be a difference among Black, Hispanic, and White students in
mathematics achievement scores. 
(5) Multiway ANOVA (Analysis of Variance) 
Several Qualitative 
Quantitative 
IVs may have 2 or more categories. 
There will be a difference among Black, Hispanic, and White, and
between male and female, students in mathematics achievement scores. 
(6) ANCOVA (Analysis of Covariance) 
1. Qualitative 2. Covariate may be either
qual. or quan., but usually quantitative 3. May also have several
additional qualitative and quantitative variables 
Quantitative 
Qualitative IVs may have 2 or more categories. Covariates used to make
adjustments to DV means. 
There will be a difference among Black, Hispanic, and White students in
mathematics achievement scores after taking into account levels of
motivation. 
7) Regression 
Both Qualitative and Quantitative 
Quantitative 

Any of the above except for chisquare. 
(9) Logistic Regression 
Both Qualitative and Quantitative 
Qualitative 
DV is qualitative with only 2 catgories 
Any of the above, except the DV will be binary (e.g., dropout/persist;
pass/fail; favor/oppose) 
Copyright 2005, Bryan W. Griffin
Last revised on