What This Document Is
This resource is a focused study guide designed to help students prepare for Midterm 2 in HS 479: Hs Pre-Intern at Western Illinois University. It centers on core concepts within research methods and statistical analysis, frequently used in fields like human services and pre-professional internships. The guide consolidates key terminology and principles essential for understanding and interpreting research findings.
Why This Document Matters
This study guide is invaluable for students aiming to solidify their understanding of foundational statistical concepts before a significant assessment. It’s particularly helpful for those who benefit from a structured review of material, or who are looking to identify areas needing further attention. Students preparing for data analysis, program evaluation, or research-based projects within their internships will find the concepts covered here directly applicable to their practical experiences. Utilizing this guide can boost confidence and improve performance on the midterm, ultimately strengthening your preparedness for professional practice.
Common Limitations or Challenges
This study guide is *not* a substitute for attending lectures, completing assigned readings, or actively participating in class discussions. It’s designed as a supplementary tool to reinforce learning, not to deliver the core course content itself. The guide focuses on defining and understanding concepts; it does not include worked examples, practice problems with solutions, or detailed explanations of complex calculations. Access to the full guide is required to gain a comprehensive understanding of the material.
What This Document Provides
* Key definitions related to descriptive and inferential statistics.
* Clarification of when to utilize different statistical measures (central tendency, dispersion).
* An overview of data distribution and its implications.
* Explanations of important statistical values like p-values and effect sizes.
* Guidance on selecting appropriate statistical tests (t-tests, correlations).
* Distinctions between variable types (continuous vs. dichotomous).
* Core concepts related to hypothesis testing and statistical power.
* Definitions of statistical terms like variance and standard deviation.