# EDEF 830

EDEF 830
Quantitative Methods

1. Catalog Entry

EDEF 830
Quantitative Methods

Credit hours (3)
Prerequisite: This class is offered for students accepted into the Doctoral Program in Education.

The primary goal of this course is to develop skills in using basic tools of quantitative research: descriptive and inferential statistics. Students will learn the mechanics of the most widely used procedures and how to use these to design and interpret educational research.

2. Detailed Description of Course

Students will learn how to use basic parametric statistics to explain results from educational research, when to apply different statistical procedures to answer research questions of interest, what assumptions underlie those procedures, and how to interpret data analyses after they have been completed. The focus of the course content will be descriptive statistics, inferences about means and inferences about relationships. This course introduces the logic and methods of statistics and how they relate to educational and behavioral sciences. Initial discussions center on the role of statistics in science, statistical designs, measurement, and how to obtain internal and external validity. The area of descriptive statistics enables students to present results and data in meaningful ways. Graphical methods and summary measures such as mean, median, standard deviation, or correlation coefficients, will be discussed. Probability concepts then lay the foundation for determining whether apparent differences in measures are likely a chance occurrence given the natural variability present in the real world. These probability concepts will be formalized into methods for drawing inferences about populations based on samples of data. The inferential procedures covered include methods for use in experimental designs with one or two samples formulated to deal with questions regarding the mean, median, proportion, or correlation in the population of interest.

• Design
• Sampling
• Measurement and graphing
• Descriptives, graphing, and variability
• Probability distributions: Norm, Z
• Sampling distributions: Central Limit Theorem
• Estimation (proportions, bias, efficiency, MI, CIs)
• Estimation (means, t, robust, sample size, CI)
• Probability intro
• Inference (general hypothesis testing, p values)
• Type I and II errors, power
• Significance tests: mean (l-sample t)
• Significance tests: proportion
• Binomial test/sign test
• Significance tests: 2 proportions
• Significance tests: 2 means
• Intro to correlation
• Explained and unexplained variability

3. Detailed Description of Conduct of Course

This course will be offered online and may include lecture, applied exercises, data analysis, case studies, and project-based learning.

4. Goals and Objectives of the Course

Upon successful completion of course requirements, students will:
• Utilize the basic tools of descriptive and inferential statistics
• Identify and enact the most widely used procedures
• Demonstrate an understanding of how to use statistics to explain results from educational research
• Apply different statistical procedures to answer research questions of interest
• Describe the assumptions that underlie statistical procedures
• Interpret data analyses after they have been completed and describe inferences based on the results of these analyses as well as limitations thereof.

5. Assessment Measures

Course assessments may include, but are not limited to, the following: leading class discussions, online discussion participation, case studies, applied project(s), and exams and/or quizzes.

6. Other Course Information

None

Review and Approval

May 2017