Structural^{[a]} Equation Modeling: An Introduction (stats is a language)……………………………....………………….……………2^{[b]}^{[c]}^{[d]}

Chapter 2: Center and Spread………………………..……………………………………..10

Univariate Data Characteristics: Mean, Median, Mode, Standard^{[e]}^{[f]} deviation, Variance, Range, Min, Max .15

Measures of association: Covariance, Correlation.……………………………………………...……………….20

Structural Equation Modeling Diagrams.…………………………………………...………………….25

Causality…………………………………...………………………….30

Standard errors, and p-values .……………………………………...……………………….35

Linear Regression .……………………………………...……………………….40More Practice ……………………………………………………………….50

Sample projects to practice your skills ………………………………….60

Common Pitfalls…………………………………………..65^{[g]}

Just a taste of more advanced statistical models that you can learn in ^{[h]}future courses…………….70^{[i]}^{[j]}

[a]I think the table of contents doesn't have all the contents listed? Also, if this is an introductory course for people with no background in statistics, the chapter titles should be something relatable and accessible to that audience. These are suggestions, and I barely know what the current chapter titles are talking about, so these might be dumb examples. Just take in the principle, please.

Chapter 1: Statistics is a language that describes relationships.

Chapter 2: Statistics gathers data about a group, but not the whole group, because that would be too much data.

Chapter 3: Statistics represents that data in graphs and charts.

Chapter 4: Statistics compares sets of data to form conclusions.

Chapter 5: Statistics can show us if one thing causes another thing.

[b]I really want a clear vision of what context you want this book to be used in. I know that you want it to be a free source textbook and that is super useful. Do they do this by themselves? With a teacher? Is it for a full year course? A half year course? This will help you know how slowly or how quickly to take the different topics. It will give you an idea of how long the book should be also. You can add more examples or less examples, more practice or less. You can design a dbl things for it too that will really help scaffold the information. It will help a lot when you are writing the chapters to have all these thoughts in mind.

[c]As a rough draft how about we assume a regular one semester University statistics class. The students will read one chapter and do the exercises for that chapter before each class? Then you will know roughly how much material to put into each chapter. Because you don't want it to be too much work or too little. Also, you will say there are usually this many classes in the semester so this is about how many chapters you want to have.

You will want the chapters to explain the topic well enough that students can work the exercises on their own after reading and they can go over sticking points or difficulties with their teacher in class. How does that feel?

That's one way to organize the book but certainly not the only way, and maybe not even the best way. What are your thoughts?

[d]@tatilarsen@gmail.com I love your comments and insights on this document. You ask fantastic questions about the learners and learning environment. Have you considered doing (or have you done) a master's in IP&T? You talk about DBL and scaffolding like a professional, so maybe you have.

[e]I think you should make this into at least 3 chapters. You can still call the chapters univariate data characteristics: mean mode and median. This would help the students understand the organization. It would even be cool to make as dbl style decision tree that shows all of statistics and you could zoom in on a certain part of the tree for each chapter in a graphic. This could show them how SEM really explains all of statistics together in one.

[f]Another great comment!

[g]Appendix: Introduction to SPSS

[h]Another thought for when the book is done, it wouldn't hurt to do a little bit of advertising for it. Introduce it to all your stats professors and collaborators, send it around to the UVU and BYU stats departments. BYU pathways might be interested. You could also send it to different high school teachers. A little work here might benefit a lot of people.

[i]I want this chapter to get them excited about all the cool things they can learn to do to solve different problems with their data. This would be best if they are problems that have come up in previous chapters and you said you can't do that or you weren't ready to address it. This could be a cool little appendix or you could do a whole chapter with examples and exercises depending on how many of these trouble shooting things there are.

[j]This is a good idea and I don't know how to wrap my head around it. What can get people excited about all the cool things they can do with statistics when those people are absolute novices in statistics, and possibly even a little afraid of it?

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