Statistics the art and science of learning from data

by Alan Agresti

KEY MESSAGE : Alan Agresti and Chris Franklin have merged their research and classroom experience to develop this successful introductory statistics text. The Art and Science of Learning from Data, Second Edition helps readers become statistically literate by encouraging them to ask and answer interesting statistical questions. It takes the ideas that have turned statistics into a central science in modern life and makes them accessible and engaging to readers without compromising necessary rigor.   KEY TOPICS : GATHERING and EXPLORING DATA; The Art and Science of Learning from Data; Exploring Data with Graphs and Numerical Summaries; Contingency, Correlation, and Regression; Gathering Data; PROBABILITY AND PROBABILITY DISTRIBUTIONS; Probability in our Daily Lives; Probability Distributions; Sampling Distributions; INFERENCE STATISTICS; Statistical Confidence Intervals; Statistical Significance Tests about Hypotheses; Comparing Two Groups; ANALYZING ASSOCIATIONS AND EXTENDED STATISTICAL METHODS; Analyzing the Association Between Categorical Variables; Analyzing the Association Between Quantitative Regression Analysis; Multiple Regression; Comparing Analysis of Variance Methods; Nonparametric Statistics   MARKET : for all readers interested in statistics.

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

Spiral-bound

First published January 1, 2006

Reviews

[Hojjat Sayyadi · Rating 5 out of 5]

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 · Rating 1 out of 5]

Gruelling and outdated.

[Jen · Rating 5 out of 5]

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 · Rating 5 out of 5]

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

[Anastasia Sidorova · Rating 4 out of 5]

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

[Sergio Uribe · Rating 5 out of 5]

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

[Giulio Ciacchini · Rating 4 out of 5]

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 · Rating 5 out of 5]

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 · Rating 4 out of 5]

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

[Judi · Rating 3 out of 5]

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 :) · Rating 4 out of 5]

good book for a math book :)

[Aukje · Rating 5 out of 5]

Nooit meer statistiek!!