HSCI 703 Quantitative Research Methods

Research design, research methods and statistical analysis are critical elements of scientific discovery. Understanding the characteristics of quantitative study design, quantitative data collection and quantitative data analysis is a cornerstone of doctoral studies. Here students will explore research design, research methods and data analysis using the foundational skills of quantitative analysis. Doctoral candidates need fundamental skills using statistical software to analyze data. In this course students will use SPSS to analyze raw data. Finally, critical analysis is a cornerstone of doctoral studies. In this course students will critically analyze data presented in peer reviewed sources.

Textbook readings and lecture presentations

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Course Requirements Checklist

After reading the Course Syllabus and Student Expectations, the student will complete the related checklist found in the Course Overview.

Discussions (4)

Discussions are collaborative learning experiences. Therefore, the student will complete four discussion assignments of at least 500 words and two replies of at least 300 words in this course. In general, these discussions are for the student’s interaction with peers rather than a focus on form (CLO: A, D). 

Study Design Analysis Assignment

Student will analyze three study designs highlighting their strengths and weaknesses (CLO: A). 

Data Collection and Transformation Project Assignment

Students will create and transform a small data set using a survey tool and transform the data for analysis (CLO: E). 

Data Analysis Projects (3)

Students will conduct analysis using SPSS or R software on data sets provided. Data analysis projects will include Student’s t-test, ANOVA and Chi-Square (CLO: B). 

Critical Analysis of Peer-Reviewed Article

Student will critically analyze the methods section of a peer reviewed article of their choosing that closely aligns with their proposed research question (CLO: C). 

Quizzes (8)