Statistics: The Art and Science of Learning from Data

by Alan Agresti, Christine A. Franklin, Bernhard Klingenberg

For courses in introductory statistics.

 

The Art and Science of Learning from Data

 

Statistics: The Art and Science of Learning from Data, Fourth Edition, takes a conceptual approach, helping students understand what statistics is about and learning the right questions to ask when analyzing data, rather than just memorizing procedures. This book takes the ideas that have turned statistics into a central science in modern life and makes them accessible, without compromising the necessary rigor. Students will enjoy reading this book, and will stay engaged with its wide variety of real-world data in the examples and exercises.

 

The authors believe that it’s important for students to learn and analyze both quantitative and categorical data. As a result, the text pays greater attention to the analysis of proportions than many other introductory statistics texts. Concepts are introduced first with categorical data, and then with quantitative data.

 

MyStatLab™ not included. Students, if MyStatLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyStatLab should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.

MyStatLab is an online homework, tutorial, and assessment product designed to personalize learning and improve results. With a wide range of interactive, engaging, and assignable activities, students are encouraged to actively learn and retain tough course concepts.

Genres: Mathematics, Psychology, Nonfiction, Academic, Reference, Textbooks, School

816 pages, Pocket Book

First published January 1, 2006

Reviews

[Hojjat Sayyadi]

آلن اگرستی تجربه 38 سال معلمی خودش رو تو این کتاب نشون داده و چه نشون دادنی. بهترین کتاب تدریس آمار و مفاهیم پایه در قرن بیست و یک. کتاب سایت محشری هم واسه درک بهتر و عملی مفاهیم آماری داره.

[Paul Pawlik]

Gruelling and outdated.

[Jen]

This was the required textbook for STAT 200 at Penn State. It was a good companion to the online lessons and I turned to it frequently for examples and alternate or better explanations of the concepts that were introduced in the instructor's online lessons. I felt it explained things clearly and in a way that helped see how all of the different tests fit together. I liked that it used examples extensively to illustrate problems and help you think them through. I'm going to keep this book for future reference and refreshing knowledge.

I actually used the looseleaf version, which I recommend for convenience. It's a heavy book and the looseleaf lets you pull out just the material that you need to read instead of having to carry the whole book.

[Mohammad]

I like it's real-world problems. especially Exit polling !!

[Anastasia Sidorova]

Very good book on statistics with a lot of examples. Descriptive and inferential statistic, but not much information on advanced statistics methods.

[Sergio Uribe]

One of the best statistical textbooks, full of real life examples and exercises.

[Giulio Ciacchini]

This textbook provides a comprehensive introduction to statistics, focusing on concepts and applications rather than complex formulas. It emphasizes the practical side of statistics while maintaining a balance with theory, making it suitable for students across various disciplines.
It is definitely, so to say, a school book which to me wasn't the best fit.

The main topics
Descriptive Statistics: Organizing and summarizing data using measures like mean, median, standard deviation, and graphical tools such as histograms and boxplots.
Probability: Basics of probability, probability distributions (like the normal and binomial), and how these underpin statistical inference.
Inferential Statistics: Estimation, confidence intervals, and hypothesis testing to draw conclusions about populations from samples.
Regression Analysis: Simple and multiple regression techniques for modeling relationships between variables.
However, more advanced topics are not explored.

Statistics is About Learning from Data: Statistics provides tools to understand patterns, summarize data, and draw meaningful conclusions. It's not just about numbers but interpreting what the data reveals about real-world situations.
Variability is Key: Understanding and managing variability in data is central to statistics. Measures like standard deviation and variance help quantify how much data points differ, enabling better insights.
Descriptive Statistics Summarize Data: Techniques like mean, median, mode, and graphical tools (e.g., histograms and boxplots) provide a snapshot of the data, making complex datasets easier to interpret.
Probability Links Data to Inference: Probability is the foundation for making predictions and drawing conclusions about populations from sample data. It bridges descriptive and inferential statistics.
Statistical Inference is Powerful: Through confidence intervals and hypothesis testing, statisticians can make predictions, estimate population parameters, and assess relationships between variables with a degree of certainty.

[Frederik Knudsen]

Fantastic read that starts with a very basic but comprehensive introduction to statistics and then gradually progresses in complexity. I wish this was the first book I picked up on the topic of statistics. I will definitely recommend it for any professional analyst because it improves your understanding of data and how you gather meaningful insights from your data.

[Harrah Hanh Tran]

Good explanation and practical examples. Just wish it could focus more on advanced research methodology.

[Judi]

It's certainly better than the statistics texts that were available when I did my undergrad. The writing is straightforward, the examples are clear, and there are a lot of practice questions.

[jag :)]

good book for a math book :)

[Aukje]

Nooit meer statistiek!!