Good introductory book on statistical/data analysis?

In summary: TL;DR Summary:The person is looking for a book on statistical analysis and data mining. They have found a book that might be good for them, but it is in Japanese. The person has looked into the book and it has chapters on statistical analysis and data mining.
  • #1
HAYAO
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TL;DR Summary: I'm looking for a book on statistical/data analysis.

Hey all. I've been doing statistical analysis in my research (such as using PCA and LDA), but I have never received a formal education on statistical analysis or data mining, and what I know about analysis is quite scattered and unorganized.

I think it is about time I get a good introductory textbook to get a broader and well-organized understanding on the topic. Could you guys recommend me a book that would be good for someone like me?

Thank you.
 
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  • #2
If you have access to a college or otherwise major library, I suggest you drop by , browse a few books and see which feels right for you. I use a rule of thumb of seeing that the book has a carefully written index, list of notation, as a reflection of having put care into writing the book.
 
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  • #3
There’s a,couple of machine learning books:
- 100 pg machine learning book by burkiv
- Hands on Machine Learning with Scikit Learn, … by Geron

that have chapters on statistical / data analysis as this is a central theme of machine learning aka statistical learning.

The 100 page book is available online from the author as a kind of try and buy scheme.

The Hands-On book has some good implementation outlines at the end to help in setting and running a machine learning project. Many of the steps would be used in data mining as well.
 
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  • #4
WWGD said:
If you have access to a college or otherwise major library, I suggest you drop by , browse a few books and see which feels right for you. I use a rule of thumb of seeing that the book has a carefully written index, list of notation, as a reflection of having put care into writing the book.
My gosh, why have I not thought of this lol. Thanks.

I'll go and see what the library has in there. The problem is, I live in Japan and many of the books are in Japanese. Of course, there are English books in there, but is probably somewhat limited compared to what you guys have in English-speaking countries.

jedishrfu said:
There’s a,couple of machine learning books:
- 100 pg machine learning book by burkiv
- Hands on Machine Learning with Scikit Learn, … by Geron

that have chapters on statistical / data analysis as this is a central theme of machine learning aka statistical learning.

The 100 page book is available online from the author as a kind of try and buy scheme.

The Hands-On book has some good implementation outlines at the end to help in setting and running a machine learning project. Many of the steps would be used in data mining as well.
Thanks. Yeah, machine learning and stuff is definitely related, but I would like to keep it more introductory. But good point about some of these machine learning books contain chapters on statistical/data analysis. Thanks for the suggestion!
 
  • #5
From your OP it was not clear to me that machine learning was your interest. But I stumbled on this PDF about applications of statistical learning that include PCA and LDA approaches.

https://www.ime.unicamp.br/~dias/Intoduction to Statistical Learning.pdf

From the introduction
Who Should Read This Book? This book is intended for anyone who is interested in using modern statistical methods for modeling and prediction from data. This group includes scientists, engineers, data analysts, or quants, but also less technical individuals with degrees in non-quantitative fields such as the social sciences or business. We expect that the reader will have had at least one elementary course in statistics. Background in linear regression is also useful, though not required, since we review the key concepts behind linear regression in Chapter 3. The mathematical level of this book is modest, and a detailed knowledge of matrix operations is not required. This book provides an introduction to the statistical programming language R. Previous exposure to a programming language, such as MATLAB or Python, is useful but not required. We have successfully taught material at this level to master’s and PhD students in business, computer science, biology, earth sciences, psychology, and many other areas of the physical and social sciences. This book could also be appropriate for advanced undergraduates who have already taken a course on linear regression. In the context of a more mathematically rigorous course in which ESL serves as the primary textbook, ISL could be used as a supplementary text for teaching computational aspects of the various approaches.
 
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  • #6
gleem said:
From your OP it was not clear to me that machine learning was your interest. But I stumbled on this PDF about applications of statistical learning that include PCA and LDA approaches.

https://www.ime.unicamp.br/~dias/Intoduction to Statistical Learning.pdf

From the introduction
This is awesome! Thank you very much.

I'm skimming through what I have in the Library, but this text covers many of what I want to learn.
 
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  • #7

1. What is the best introductory book on statistical/data analysis?

The best introductory book on statistical/data analysis will depend on your specific needs and background. Some popular options include "An Introduction to Statistical Learning" by Gareth James et al., "The Data Science Handbook" by Field Cady, and "Data Analysis: A Bayesian Tutorial" by Devinderjit Sivia and John Skilling.

2. What topics should a good introductory book on statistical/data analysis cover?

A good introductory book on statistical/data analysis should cover basic statistical concepts, data collection and cleaning techniques, exploratory data analysis, hypothesis testing, regression analysis, and data visualization. It may also cover more advanced topics such as machine learning and Bayesian statistics.

3. Is it necessary to have a strong background in math to understand a good introductory book on statistical/data analysis?

While a basic understanding of math is helpful, it is not always necessary to have a strong background in math to understand a good introductory book on statistical/data analysis. Many books provide clear explanations and examples that make the concepts accessible to those without a strong math background.

4. Are there any online resources that can supplement a good introductory book on statistical/data analysis?

Yes, there are many online resources that can supplement a good introductory book on statistical/data analysis. Some popular options include online courses such as Coursera's "Introduction to Data Science" and "Data Analysis and Statistical Inference" by Duke University, as well as YouTube channels such as Khan Academy and StatQuest.

5. How can I determine if a book on statistical/data analysis is suitable for my level of understanding?

You can determine if a book on statistical/data analysis is suitable for your level of understanding by reading reviews and looking at the book's table of contents. It may also be helpful to preview a few chapters or sections of the book before purchasing it. Additionally, you can consult with a colleague or mentor who has a similar background to yours for their recommendation.

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