Chapter 1: The Need for Good Data.- Chapter 2: Basic Data Types and When to Use Them.- Chapter 3: Representing Quantitative Data.- Chapter 4: Planning Your Data Collection and Analysis.- Chapter 5: Good Datasets.- Chapter 6: Good Data Collection.- Chapter 7: Dataset Examples and Use Cases.- Chapter 8: Cleaning your Data.- Chapter 9: Good Data Anayltics.- Appendix A: Recommended Reading.
Harry J. Foxwell is a professor. He teaches graduate data analytics courses at George Mason University in the department of Information Sciences and Technology and he designed the data analytics curricula for his university courses. He draws on his decades of experience as Principal System Engineer for Oracle and for other major IT companies to help his students understand the concepts, tools, and practices of big data projects. He is co-author of several books on operating systems administration. He is a US Army combat veteran, having served in Vietnam as a Platoon Sergeant in the First Infantry Division. He lives in Fairfax, Virginia with his wife Eileen and two bothersome cats.
“The book is definitely valuable and anyone involved in statistical studies would do well to read it. The text could also be a useful tool in a graduate analysis course. The writing is clear and to the point, with no unnecessary ‘preaching’.” (James Van Speybroeck, Computing Reviews, September 2, 2021)
 |
Ask a Question About this Product More... |
|
