- [Curt] Thanks again for working through the course with me. I hope you've gotten a lot out of it. As with many subjects, there are a lot more avenues that you can pursue with data analysis. So before I go, I'd like to provide three resources to which you can refer. The first is a book called Statistics for People Who (Think They) Hate Statistics by Neil Salkind, from Sage Publications. It's an excellent book and it was written by a former professor of child psychology at the University of Kansas, also a good friend. And his book is outstanding as an introduction for people who are more attuned perhaps to the poet side instead of the quant side of analysis.
Next is the book Head First Data Analysis by Michael Milton. This is part of the Head First series from O'Reilly, and it is extremely visual. So if you're a visual person, and you want some background and context on data analysis beyond what I've covered in this course, I highly recommend this book and that approach. And finally, Data Analysis and Business Modeling by Wayne Winston, from Microsoft Press. There are actually several different editions of this book, some for numbered versions of Excel, such as 2016 or 2019, and previous versions as well.
This book, which is substantial, provides a lot of different techniques that you can use to answer specific types of questions. So while the first few books are for individuals who want a broader explanation of data analysis at the conceptual level with some techniques, Data Analysis and Business Modeling is much more focused on showing you how to perform certain types of analysis. Thanks again. I hope you've enjoyed the course, and I look forward to working with you again.
- Distinguish between the mean, median, and mode.
- Describe the relationship between variance and standard deviation.
- Identify a nondirectional hypothesis.
- Point out the difference between COVARIANCE.P and COVARIANCE.S.
- Explain correlation.
- Analyze Bayes’ rule.