Introductory Statistics

Program Overview

Introductory Statistics (HSTATS-451-DL) is a fully asynchronous online course that introduces students to fundamental statistical concepts. The course emphasizes conceptual understanding and covers topics such as organizing data, measures of central tendency, probability, sampling, and statistical hypothesis testing. It is suitable for individuals seeking a foundation in statistics for health-related fields, preparing for graduate studies in health professions, or working professionals who need statistical knowledge for data analysis in healthcare settings.

Program Outline

Outline:

Course Description:

This course introduces students to fundamental statistical concepts. Topics covered include:

• Organizing data
• Measures of central tendency
• Probability
• Sampling
• Statistical hypothesis testing

Format:

This is a fully asynchronous online course with no required meeting times. Course materials are organized into modules typically spanning one week. Students can adjust their schedule to fit the learning activities within their own timeframe.

Course Schedule:

The course is offered three times per semester. Students can choose to take it over the full semester or during a 6-week accelerated term.

• Summer 2024 Traditional (DL): May 28 - August 19
• Summer 2024 Intensive A (DL2): May 28 - July 8
• Summer 2024 Intensive B (DL3): July 9 - August 19
• Fall 2024 Traditional (DL): September 3 - December 6
• Fall 2024 Intensive A (DL2): September 3 - October 18
• Fall 2024 Intensive B (DL3): October 22 - December 6

Course Activities:

Each week includes a combination of self-directed learning, self-assessment, assignments, and discussion board participation.

• Self-Directed Learning: Reading textbooks, articles, watching mini-lectures, videos, and listening to podcasts (3-4 hours/week)
• Self-Assessment: Mini quizzes, practice problems, and weekly module assessments (2-3 hours/week)
• Assignments: Written papers, case studies, and practical assignments (3-4 hours/week)
• Discussion Boards: Initial posting, reading posts, and responding to peers (3-4 hours/week)

Total time commitment:

Approximately 10-15 hours per week.

Course Topics:

• Defining health profession-related variables
• Types of scales: nominal, ordinal, interval, and ratio
• Hypothesis testing fundamentals
• Using SPSS for data entry, analysis, and processing
• Generating descriptive statistics and measures of central tendency
• Describing data distribution (mode, symmetry, skew)
• Variability measurement and standard deviation
• Assessing correlation (positive
  egative) using Pearson's r test
• Comparing group means with t-tests and ANOVA analysis
• Longitudinal data analysis using repeated-measures ANOVA
• Non-parametric testing (binomial, crosstab analyses)

Teaching:

Faculty:

KaRynn Sheranian, MS, CCC-SLP is a PhD student, Lecturer in Speech Language and Acquisition, and instructor for this course.

Teaching Methods:

The course utilizes various teaching methods, including:

• Mini-lectures and video presentations
• Reading assignments from textbooks and articles
• Self-assessment quizzes and practice problems
• Group discussion boards
• Practical exercises and case studies
• SPSS software tutorials

Technology Requirements:

• Access to D2L online learning platform
• Web browser with compatibility verified as per D2L system recommendations
• Ability to video conference (recommended)

Other:

Course Materials:

• D2L platform access is required
• Web-based Learning Application: Required (may vary by semester and involve separate registration)

This course is suitable for individuals:

• Seeking a foundation in statistical concepts for health-related fields
• Preparing for graduate studies in health professions
• Working professionals who need statistical knowledge for data analysis in healthcare settings