Isbn: 9781098190255 - think stats: exploratory data analysis (12 Ergebnisse)

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. In English.

Zustand: New.

Zustand: New. 2025. 3rd ed. paperback. . . . . . Books ship from the US and Ireland.

Paperback. Zustand: Brand New. 3rd edition. 226 pages. 9.19x7.00x9.19 inches. In Stock.

Zustand: NEW.

Zustand: New.

Taschenbuch. Zustand: Neu. Neuware - If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you'll learn the entire process of exploratory data analysis--from wrangling data and generating statistics to identifying patterns and testing hypotheses. Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter not Elektronisches Buch, so you can read the text, run the code, and work on exercises all in one place. - Analyze data distributions and visualize patterns using Python libraries - Improve predictions and insights with regression models - Dive into specialized topics like time series analysis and survival analysis - Integrate statistical techniques and tools for validation, inference, and more - Communicate findings with effective data visualization - Troubleshoot common data analysis challenges - Boost reproducibility and collaboration in data analysis projects with interactive not Elektronisches Buch.…

Taschenbuch. Zustand: Neu. Think Stats | Exploratory Data Analysis | Allen Downey | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | O'Reilly Media | EAN 9781098190255 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. …

Taschenbuch. Zustand: Neu. Neuware -If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you'll learn the entire process of exploratory data analysis--from wrangling data and generating statistics to identifying patterns and testing hypotheses. Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter not Elektronisches Buch, so you can read the text, run the code, and work on exercises all in one place. - Analyze data distributions and visualize patterns using Python libraries - Improve predictions and insights with regression models - Dive into specialized topics like time series analysis and survival analysis - Integrate statistical techniques and tools for validation, inference, and more - Communicate findings with effective data visualization - Troubleshoot common data analysis challenges - Boost reproducibility and collaboration in data analysis projects with interactive not Elektronisches BuchLibri GmbH, Europaallee 1, 36244 Bad Hersfeld Englisch.…

Taschenbuch. Zustand: Neu. Neuware -If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you'll learn the entire process of exploratory data analysis--from wrangling data and generating statistics to identifying patterns and testing hypotheses. Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter not Elektronisches Buch, so you can read the text, run the code, and work on exercises all in one place. - Analyze data distributions and visualize patterns using Python libraries - Improve predictions and insights with regression models - Dive into specialized topics like time series analysis and survival analysis - Integrate statistical techniques and tools for validation, inference, and more - Communicate findings with effective data visualization - Troubleshoot common data analysis challenges - Boost reproducibility and collaboration in data analysis projects with interactive not Elektronisches Buch Englisch.…