Intermediate Statistical Methods in Education

Student Learning Outcomes, Goals, Objectives:

Students successfully completing this course will be able to:

• Be able to define basic statistical terminology and apply those concepts to quantitative research studies

• Understand statistical notation and definitional formulas and apply computational statistical formulas to small data sets

• Be able to statistically describe a set of data using exploratory data analysis

• Understand the purpose, utility and properties of the standard normal distribution

• Examine and understand the theoretical foundations of statistical hypothesis testing from the perspective of sampling theory

• Develop an applied understanding of and appreciation for the concept of probability and its role in hypothesis testing

• Understand how to compare and test goodness-of-fit and associative hypothesis about categorical grouping variables using chi-square analysis

• Understand how to formulate and test statistical hypotheses about a single group mean using z-tests (known variance) and t-tests (sample-estimated variance)

• Extend understanding of the concept of hypothesis testing to formulating and testing statistical hypotheses about means involving paired/matched/dependent samples (e.g. pre- post comparisons) and means for two independent sample groups

• Understand the concept of statistical power and its connection to sampling theory and hypothesis testing

• Understand covariance and the Pearson product-moment correlation coefficients as a index of statistical association

• Understand the research context and apply simple linear regression for modeling predictive or explanatory bivariate relationships

• Demonstrate basic knowledge, skill and ability competencies as a consumer of quantitative data with the capability to designing a basic statistical study (sampling and hypothesis testing), analyze the data, and interpret/present the results

Course Grading Information:

Activity/Performance Measure	Percentage/Points
Assigned homework and quizzes consist of engaging in lectures/discussion and completing all assigned homework problems	40%
Midterm examination will consist of several computational problems that require students to select and carry out a statistical analysis and briefly interpret the results	30%
Final examination will comprise six to seven computational problems that require students to select and carry out the appropriate statistical analysis and then briefly interpret the results	30%

Attendance/Participation:

Participation is a graded component included in the student's final grade for this course.

Course Materials Purchased by the Students:

Field, Andy. (2024). Discovering Statistics Using IBM Statistics, 6th Edition. Sage Publications. (ISBN-1529630002 or ISBN-13: 978-1529630008).