﻿ EDUR 8131
 EDUR 8131 Educational Statistics 1 (4 Week Format) Summer 2012 Instructor: Bryan W. Griffin (bwgriffin@GeorgiaSouthern.edu) My personal web pages: http://coe.georgiasouthern.edu/foundations/bwgriffin/

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)

1. Syllabus
3. Course Calendar
4. Reporting statistical results in APA style: http://www.bwgriffin.com/gsu/courses/edur8131/content/reporting_statistics_sept_2009.doc
5. Sample Test 1 (material through one-sample t-test)
6. Sample Test 2 (shows examples of data analysis section of Test 2 with t-tests, correlation, and chi-square; Sample Test 2 Answers)
7. Test 1: Covers content found in Notes 1, 2, 3, and 4. Test 1 may be posted as early as 5/24 or 5/29.
8. Test 2: Covers content found in Notes 1 through 7. Test 2 may be as early as 6/5 or 6/7.
9. Test 3: Covers all content found in Notes 1 through 9d. Test 3 may be posted by 6/14 and responses due 6/19.
10. Exercises
1. Central Tendency, Variability, Graphical Displays (with answers)
3. Z scores, Percentile Ranks, and Z test (with answers)
4. One and Two Samples t-test (answers)
6. One Sample, Two Samples, and Correlated t-tests (with answers)
9. ANOVA (answers note this is a Word Document)
10. Regression (see regression notes)
1. Lecture Notes and Videos
1. Notes 1 Descriptive Statistics
2. Notes 2 Normal Distribution and Standard Scores
3. Notes 3 Statistical Inference
4. Notes 4 Hypothesis Testing and One Sample Z Test
5. Notes 5 t-tests (note, update CI for one sample t-test)
• Excel files:
• Critical t-values table: t-tables.pdf
6. Notes 6 Correlation (note, use car data to illustrate correlation matrix in SPSS)
7. Notes 7 Chi-square
8. Notes 8a Simple Regression
9. Notes 8b Multiple Regression
10. Notes 9 ANOVA
11. Notes 9d ANCOVA
Sample Data
1. Types of Statistical Procedures and Their Characteristics: PDF Table and written Step-by-step Procedure
2. SPSS Tutorials (obtained from various on-line sources: Dr. McKnight at U. Oklahoma,  Dr. Elvers at U. of Dayton, Guang-Hwa Change at Youngstown State U.)
1. Entering data into SPSS (variable labels, value labels, setting variable as numeric, etc.)
Data Entry A, Data Entry B
2. Frequencies/Explore Commands (including descriptive statistics, box plots, histograms, stem-and-leaf, etc.)
Frequencies A, Frequencies B, Stem and Leaf, Various Graphical Displays
3. t-tests (one sample, independent sample, and correlated samples)
t-tests, independent samples t-tests
4. Correlation
Correlation A, Correlation B, For scatter plots see Various Graphical Displays above
5. Chi Square
Goodness of Fit  and Test of Association; other examples:  Goodness of Fit A, Goodness of Fit B (note this is a Word document),  Test of Association
6. Regression
Regression A, Regression B
7. ANOVA
ANOVA A (using ONEWAY command), ANOVA B (using ONEWAY command), ANOVA C (using UNIVARIATE command)
8. ANCOVA
ANCOVA A
1. On-line Statistical Resources
2. Course Assessment Questionnaire (may be used to collect data to illustrate statistical analysis)

 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 402-403 Pages 374-376 Pages 362-364 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 1 Chapter 1 Chapter 1 6. Central Tendency Chapter 1 Chapter 1 Chapter 1 7. Variability Chapter 1 Chapter 1 Chapter 1 8. Standard Scores Chapter 1 Chapter 1 Chapter 1 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 z-test Chapter 6 Chapter 6 Chapter 6 12. t-test (one-sample, independent samples, correlated) Chapter 7 Chapter 7 Chapter 7 13. Correlation (Pearson r) Chapter 2, 10 Chapter 2, 10 Chapter 2, 10 14. Chi-square (c2) (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

1. Syllabus
2. Notes 1
3. Notes 2
4. Notes 3

Session 2 (5/24): 5pm to 9:00pm

1. Resume Notes 2, if needed
2. Notes 3
3. Notes 4

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

1. Resume Notes 4, if needed
2. Notes 5
3. Notes 6

Session 4 (5/31): 5pm to 9:00pm

1. Resume Notes 5 or 6, if needed
2. Notes 6
3. Notes 7

Session 5 (6/5): 5pm to 9:00pm

1. Resume Notes 6, if needed
2. Notes 7
3. Notes 8a

Test 2 posted sometime after Session 5 (assuming coverage of chi-square is completed [Notes 7], otherwise Test 2 posted after Session 6)

Session 6 (6/7): 5pm to 9:00pm

1. Resume Notes 7, if needed
2. Notes 8a
3. Notes 8b

Session 7 (6/12): 5pm to 9:00pm

1. Resume Notes 8b, if needed
2. Notes 9
3. Notes 9

Session 8 (6/14): 5pm to 9:00pm

1. Resume Notes 9, if needed
2. Notes 9d

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) t-test for independent groups Qualitative Quantitative IV has only 2 categories There will be a difference between boys and girls on mathematics achievement scores. (3) Chi-Square 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) One-way 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) Multi-way 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 chi-square. Special coding procedures are required to in regression to handle qualitative IVs. (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)