Choosing the Right Statistical Test Guide
Area IV — Conducting Evaluation and ResearchTL;DR
This lesson covers choosing the right statistical test guide as part of Area IV — Conducting Evaluation and Research. Key topics include overview of common statistical tests: t-test, anova, chi-square, correlation, regression, how to match the test to the research question and data type, parametric vs non-parametric tests. Focus on understanding how these concepts are applied in real-world health education scenarios and how NCHEC frames them in exam questions.
In Video 45 of the CHES & MCHES certification prep series, we take an in-depth look at choosing the right statistical test guide. This lesson falls under Area IV — Conducting Evaluation and Research, one of the core competency areas defined by the National Commission for Health Education Credentialing (NCHEC). Whether you are preparing for your initial CHES certification or advancing to the MCHES level, mastering this content is essential for exam success and professional practice.
This video helps you choose the right statistical test for different research scenarios. Knowing which test to use is a common topic on the CHES and MCHES exams.
Area IV focuses on Conducting Evaluation and Research Related to Health Education. This area tests your knowledge of evaluation design, data analysis, and evidence-based decision making. Understanding both formative and summative evaluation is essential for demonstrating program effectiveness.
Understanding overview of common statistical tests: t-test, anova, chi-square, correlation, regression is a key component of this competency area. The NCHEC expects certified health education specialists to demonstrate not only theoretical knowledge of this concept but also the ability to apply it in real-world public health scenarios. Understanding how to match the test to the research question and data type is a key component of this competency area. The NCHEC expects certified health education specialists to demonstrate not only theoretical knowledge of this concept but also the ability to apply it in real-world public health scenarios. Understanding parametric vs non-parametric tests is a key component of this competency area. The NCHEC expects certified health education specialists to demonstrate not only theoretical knowledge of this concept but also the ability to apply it in real-world public health scenarios. Understanding decision flowchart for selecting statistical tests is a key component of this competency area. The NCHEC expects certified health education specialists to demonstrate not only theoretical knowledge of this concept but also the ability to apply it in real-world public health scenarios. Understanding practice scenarios for exam preparation is a key component of this competency area. The NCHEC expects certified health education specialists to demonstrate not only theoretical knowledge of this concept but also the ability to apply it in real-world public health scenarios.
This topic appears frequently on the CHES and MCHES certification exams. Scenario-based questions in this area often require you to identify the most appropriate course of action given a specific public health context. Pay close attention to the distinctions between similar concepts, as NCHEC exam writers frequently use closely related answer choices as distractors. Reviewing this material alongside practice questions will help reinforce your understanding and improve your test-taking confidence.
As you work through this content, consider how each concept connects to the broader health education process. The NCHEC exam blueprint emphasizes the integration of knowledge across all Areas of Responsibility. A strong candidate understands not only the individual competencies but also how assessment, planning, implementation, evaluation, advocacy, communication, leadership, and ethics work together in professional practice. Use this video lesson as a starting point, then deepen your understanding through additional study resources available at subthesis.com.
Key Topics Covered
- Overview of common statistical tests: t-test, ANOVA, chi-square, correlation, regression
- How to match the test to the research question and data type
- Parametric vs non-parametric tests
- Decision flowchart for selecting statistical tests
- Practice scenarios for exam preparation