EDUR 8131 Summer 2012 Instructor: Bryan W. Griffin (bwgriffin@GeorgiaSouthern.edu) 
Announcements 
Linked sample data files (SPSS) below Notes 8a: Simple Regression.
Added page Identifying Statistical Procedures (see point 12 in Course Index)
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)
 Central Tendency, Variability, Graphical Displays (with answers)
 Displaying Data (with answers)
 Z scores, Percentile Ranks, and Z test (with answers)
 One and Two Samples ttest (answers)
 Correlated Samples ttest (answers)
 One Sample, Two Samples, and Correlated ttests (with 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
 Displaying Data (frequency distributions, stemandleaf, bar charts, histograms, pie charts, box plots, scatterplots)
 Instructional Videos and Related Materials
 Supplemental Notes Displayed in Videos
 Supplemental Excel File Displayed in Videos
 Section 1: Descriptive vs. Inferential Statistics (also SPSS data entry explained)
 Section 2: Variables
 Section 3: Scales of Measurement
 Section 4: Types of Variables
 Section 5: Hypotheses
 Sections 6, 7, and 8: Central Tendency (also SPSS showing descriptive statistics)
 Section 9: Distributions and Central Tendency
 Section 10: Mean of Groups
 Section 11: Inference and Sampling Error
 Sections 12 and 13: Measures of Variability (also SPSS examples)
 Section 14: Frequency Distribution and Percentile Ranks (SPSS examples) to be added
 Section 15, 16, 17: Graphical Displays (SPSS examples) to be added
 Supplemental Videos
 Averages: On Average, Swedes have 1.99 Legs (4 minutes)
 Pie Chart (Polar Area Display): Showing the Dead: Which is more Deadly, Battlefield or Hospital? (4 minutes)
 Scatterplot: Life Expectancy and Wealth over 200 Years (4 minutes)
 Supplemental Reading and Exercises:
 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)
 Overview of things to come; read on your own  Descriptive Statistics and Graphical Displays (correlation coefficients and scatterplots) and Inferential Statistics (practice exercise)
 Notes 2 Normal Distribution and Standard Scores
 Z table (left side probabilities)
 Normal Distribution with Corresponding Relative Scores (review this, a useful image)
 Normal Distribution image (used for plotting Z scores during chats)
 Instructional Videos and Related Materials
 Supplemental Notes Displayed in Videos
 Sections 1 and 2: Standard Scores and Zscore Interpretation
 Section 2: Zscore Calculation from Raw Data
 Section 3: Finding Area Under Normal Distribution
 Section 4: Finding Area for a Raw Score
 Section 5: Calculating Percentile Ranks
 Section 6: Convert from X to Z
 Sections 7, 8, and Common Areas: Skewness, Kurtosis, and Common Area
 Supplemental Readings:
 Probability and finding area under standard normal curve (Excel table with area to left of Z: Z Table); below is information on calculating area under normal curve:
 Additional Coverage of Notes 2 Material:
 Notes 3 Statistical Inference
 Excel file: 2. Population, Sample, and Sampling Distributions
 Supplemental Reading:
 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
 Additional Coverage of Hypothesis Testing
 Notes 4 Hypothesis Testing and One Sample Z Test
 Instructional Videos and Related Materials
 Supplemental Excel File Show in Videos
 Section 1: Logic of Hypothesis Testing with a Fair Coin
 Section 2a: Onesample Z TestHypotheses
 Section 2b: Onesample Z TestCalculating pvalues
 Section 2c: Onesample Z TestDecisions Regarding Ho
 Section 2d: Onesample Z TestSummary and Additional Examples of Z Test
 Section 3: Shortcuts to Calculating pvaluesRejection Regions
 Sections 4 and 5: Errors in Hypothesis Testing (and assumptions of Z Test)
 Section 6: Power
 Supplemental Reading:
 Notes 5 ttests (note, update CI for one sample ttest)
 Excel files:
 Critical tvalues table: ttables.pdf
 Supplemental Readings:
 Notes 6 Correlation (note, use car data to illustrate correlation matrix in SPSS)
 Excel files: Correlation
 Critical Pearson r values table: critical r
 Video  Correlation and Causation: English is the Cause of Death (4 minutes)
 Supplemental Readings:
 Read this: Correlation Coefficients and Scatterplots
 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
 Notes 7 Chisquare
 Excel files:
 Online Chisquare Calculators:
 http://faculty.vassar.edu/lowry/newcs.html (test of association; Important  specify number of rows and columns to get correct df and p)
 http://faculty.vassar.edu/lowry/csfit.html (goodnessoffit)
 Supplemental Readings:
 Notes 8a Simple Regression
 Sample data files (each is an SPSS file):
 Critical F ratio: http://www.bwgriffin.com/gsu/courses/edur8132/notes/critical_f_values.pdf
 Notes 8b Multiple Regression
 Regression Coefficient Interpretation
 Critical F ratio: http://www.bwgriffin.com/gsu/courses/edur8132/notes/critical_f_values.pdf
 Videos and Related Material
 01 Purpose, Equation, and Partial Effects
 02 Partial Effects
 03 Partial Effects Part 2
 04 Residuals and Literal Interpretation
 05 Ice Cream Example
 06 House Price Example
 07 Model Fit
 08 Inference
 09 Confidence Intervals (Short video showing Confidence Interval with SPSS with difference confidence levels)
 10 APA Styled Results (Word document of House Price Example in APA Style )
 place holder
 Notes 9 ANOVA
 Multiple Comparisons in Excel: Bonferroni and Scheffe
 ANOVA Group Separation Example: http://www.buseco.monash.edu.au/mkt/resources/applets/onewayanova.html
 Multiple Comparisons in Zoho (online spreadsheet): Bonferroni and Scheffe (this spreadsheet does not work correctly)
 Critical F ratio: http://www.bwgriffin.com/gsu/courses/edur8132/notes/critical_f_values.pdf
 Supplemental Reading:
 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 (not covered in EDUR 8131 this semester)
 Video Tutorial: Oneway ANCOVA with Factor*Covariate Interaction (Unfortunately sound spikes and breaks occasionally; not covered in EDUR 8131 this semester)
 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 (tentative projection of content coverage; will be revised throughout term)
Session 1 (5/22): 5pm to 9:00pm
Session 2 (5/24): 5pm to 9:00pm
Test 1 posted sometime after Session 2 (assuming Notes 4 is completed, otherwise Test 1 posted after Session 3)
Session 3 (5/29): 5pm to 9:00pm
Session 4 (5/31): 5pm to 9:00pm
Session 5 (6/5): 5pm to 9:00pm
Test 2 posted sometime after Session 5 (assuming coverage of chisquare is completed [Notes 7], otherwise Test 2 posted after Session 6)
Session 6 (6/7): 5pm to 9:00pm
Session 7 (6/12): 5pm to 9:00pm
Session 8 (6/14): 5pm to 9:00pm
Test 3 will be posted sometime around 6/14
Test 3 responses due 6/19
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. 
(8) Logistic Regression 
Both Qualitative and Quantitative 
Qualitative 
DV is qualitative with only 2 categories 
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 10 September, 2012 10:47 AM