EDLD579 Inferential Statistics (2 units)
Instructor: Noriyuki Inoue, Ph.D.
Email : inoue@sandiego.edu
Office: AW 2-107
Telephone: 619-260-7669
Course Description
This is a 2 unit course in inferential statistics, encompassing the hypothesis testing of the mean, ANOVA, the chi square test, and an introduction to multiple linear regression. This course is aimed at the doctoral candidates in education and leadership studies. As such, particular emphasis is placed on understanding statistical procedures commonly used in quantitative research in the field of education and leadership studies and applying it to the inferential analyses of the quantitative data.
The course incorporates the statistical analysis components of the SPSS software package. SPSS is accessible via computers located in Serra 185, Maher 114, and Alcala West 229. Additionally, students in this course are encouraged to obtain the Student Version of the package to load onto their personal computers. There will be a tutorial scheduled on Saturday, February 12 from 10:00 – 12:00. Students are encouraged to attend the tutorial session.
Since this is an inferential statistics, a basic understanding of descriptive statistics is required. To enroll in this course, you need to have completed a graduate level descriptive statistics course.
Textbooks/Readings/Software
Textbook
Hinkle, D. E., Wiersma, W., & Jurs, S. G. (2003). Applied Statistics for the Behavioral Sciences (5 th Ed.).
New York: Houghton Miffilin. (Required)
The following two items are not required, but I strongly encourage you to obtain these items not only for this class, but also for your dissertation work.
SPSS student version (available at USD bookstore).
George, D., & Mallery, P. (2002). SPSS for Windows Step by Step : A Simple Guide and Reference
Additional readings may be handed out in class.
Course Requirements/Activities
Class participation: You are required to actively participate in class discussions, online activities, project presentations and Saturday review sessions. Your preparation for the class and active contribution to the class constitutes an essential part of the learning activity in the course.
Assignments : Occasionally, you will be given assignments. The assignments could be either take home or in class assignments. There will be no make up for the in-class assignments. Please make sure that you attend all the sessions to complete them.
Problem solving presentation: You will give at least one problem solving presentation in class. There, you will explain the problem, present the problem solving process to the class, and explain key concepts and procedures for the other students. It is recommended that you will consult your instructor or tutor on the problem solving if there is any ambiguity in your understanding. The use of visual information (such as
PowerPoint and overhead slide) is required.
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Group project
You will form a group of 3-4 with your peers for the group project. First, a hypothetical data set is given to you, and you will analyze the data by applying the inferential methods discussed in class. Your 3-5 page group project paper should include the introduction, the analyses, the interpretation of your analyses in terms of educational/policy implications. A PowerPoint presentation of your project is required. Your paper is due one week after your presentation.
Final exam
There will be a final exam that covers the entire class. The exam is in-class, open textbook, and open laptop/calculator exam. The examples of exam problems will be presented and explained in advance.
( Extra point project : You are encouraged to propose an extra point project of your own. The proposal must be approved by the instructor before you actually work on the project. Be creative in devising interesting and substantial projects. The points you can add with the extra point project depend on the quality of your project. This is not a mandatory assignment.)
Assessment Plan/Grading Criteria/Rubric
The final grade is calculated based on the following criteria:
Class participation: 10%
Assignments: 30%
Problem solving presentation: 10 %
Group project: 20%
Final exam: 30%
The following table shows the correspondence between letter grades and 100 point scale scores.
Letter grade 100 pt score Equivalent score
A
A-
B+
B
B-
C+
C
94-
90-93
87-89
83-86
80-82
76-79
73-75
96
92
88
85
81
78
74
C-
D+
D
D-
F
69-72
66-68
63-65
60-62
0-59
71
67
64
61
0
Course Outline
Dates
Week 1
Week 2
Week 3
Topics
Course orientation/Introduction
Normal and Sampling Distributions
Hypothesis Testing: One Sample Case I
Hypothesis Testing: One Sample Case II
Hypothesis Testing: Two Sample Case I
Reading assignments
Chap. 7 (p.141-p.153, p.160-p.173)
Chap. 8, 9
Chap. 10
Chap. 11
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Week 9
Week 10
Week 11
Week 4
Week 5
Week 6
Week 7
Week 8
No class - Spring break
Hypothesis Testing: Two Sample Case II
Group Project presentation I
No class – Library day-
Chi-Square Tests
One-way Analysis of Variance
Group Project presentation III
Two-way Analysis of Variance
Group Project presentation IV
Analysis of Variance: Synthesis
Linear Regression
(+Multiple Linear Regression,
Analysis of Covariance)
Group Project presentation V
Final Exam
-
Group Project presentation II
Chap. 12, 13
Chap. 21
Chap. 14, 15
Chap. 16
Chap. 16
Chap. 6
(Chap. 17, 18
Chap. 19)
Other information
Cancellation of class
The class might be canceled due to unavoidable reasons. Also, your instructor may be late or cannot come to class due to unforeseeable reasons. In case no information is given to you and the instructor does not come to class for 20 minutes, please regard the class was cancelled. If a class was canceled, the assignment due in the class will be due next time.
Disabilities
If you have a special need that may effect learning activities, please notify the instructor at the beginning of the course. Special arrangements could be made depending on the need and condition.
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