1.3 Course Structure
Objectives
Nearly every section will include an Objectives box at the top. This box will detail the primary objectives of the section. It is good to review this box prior to processing the content in that section. This will anchor your expectations and learning.
Key Terms
Key terms within the text will be highlighted in blue like this: key term. Hovering your mouse over the key term (or single tapping if on a touchscreen device) will display a little tip bubble to briefly define the key term. A full list of these key terms can be viewed in the glossary, accessible from the right-side tool panel.
Datasets and Models
A small box will appear at the top of nearly every section, just below the Objectives box. This box will contain any relevant datasets (usually .sav files for SPSS) or AMOS models (usually .amw files). Each will be labeled appropriately so you will know specifically what to use them for.
Reading
Every section will include an explanation of topics relating to SEM. These readings will provide context and background to all analytical procedures so that you can understand more than how to do SEM. After each section, you should also know why to use a particular analytical procedure and what it means. Understanding why and what is important enough that these will also be assessed at the end of each section. Knowing how to do an analysis without understanding why is more dangerous than not knowing how to do an analysis. Understanding why, and knowing what it means, is more important than knowing how to do it. I can automate most of the procedural (click and type) components of SEM. Knowing when to apply which analysis and what it means is the more important (hard to automate) portion of learning.
References
For every section, I will provide a list of relevant references. These will appear at the top of the section in their own box, right under the Datasets and Models box. There are, in many cases, dozens or even hundreds of possible citations. The ones I include are the ones I am familiar with and that I know support the approaches I'm teaching. If you know of other possibly more appropriate citations, please feel free to email them to me here: james.gaskin@byu.edu. I maintain a large list of citations (StatWiki References) for a lot of what you will learn in this course.
Examples
Each topic that covers analytical approaches to statistics or SEM will also include examples. These examples will be shown in videos. I strongly encourage you to not only watch the example videos, but also to do the videos by following along with the datasets and models provided at the top of the page. Doing the videos will reinforce the material much better than simply watching the video.
Exercises
Each topic that covers analytical approaches to statistics or SEM will also include exercises that can be done using the datasets and models provided at the top of the page. These exercises will often go hand-in-hand with the assessments. For example, in the exercise I will have you run a causal model and then in the assessment I will ask you to select the coefficient for a particular relationship. Exercises are good practice and will help to synthesize the topics covered in that section.
Quick Summary
Some sections will include a "Quick Summary" at the bottom, just after all the readings, examples, and exercises, but before any assessments. These quick summaries are video explanations of the section's content. These videos will not be as thorough as the readings, and so they are not intended to replace the readings. Instead, they just quickly summarize the readings so that you can get one more pass at the information, hopefully further solidifying the concepts. These also act as a good refresher if you return to the section after a long absence. While some quick summaries will be included at the bottom of a section, others will have their own section, and will summarize all sections in the entire chapter.
Assessments
Each topic will conclude with an assessment. These assessments are critical to test your understanding of the material, as well as to test your ability to execute statistical analyses. As such, assessments will include conceptual questions as well as analytical questions. I want to make sure you not only know how to run the appropriate analysis, but that you also know which analysis is most appropriate and why and what the output of the analysis actually means.