Synopses & Reviews
Lock's first edition of
Statistics: Unlocking the Power of Data incorporates the use of available technologies and modern methods of data analysis. The text focuses on providing conceptual understanding of the main themes of statistical inference (with the help of a strong emphasis on the use of technology), to provide a more solid grasp of the core ideas of statistics and make it relatively easy to apply those ideas to more theoretical and advanced statistics topics.
Furthermore, the text offers cutting edge ideas like randomization and bootstrapping to introduce the fundamental ideas of statistical inference to enhance understanding, make statistics come alive, and deliver improved retention. There is also an emphasis on current, real data and real-life applications along with a seamless integration between text and simulations, animated graphs, and technology-specific data tables.
The Lock text is the first written from the ground up utilizing both instructional technology and modern methodology like the bootstrap method to set it apart as the introductory statistics program of the 21^{st} century.
Synopsis
This book incorporates the use of available technologies and modern methods of data analysis. The text focuses on providing conceptual understanding of the main themes of statistical inference, to provide a more solid grasp of the core ideas of statistics and make it relatively easy to apply those ideas to more theoretical and advanced statistics topics. Furthermore, the text offers cutting edge ideas like randomization and bootstrapping to introduce the fundamental ideas of statistical inference to enhance understanding, make statistics come alive, and deliver improved retention.
Table of Contents
Unit A: DataChapter 1: Collecting Data
Chapter 2: Describing Data
Unit B: Understanding Inference
Chapter 3: Confidence Intervals
Chapter 4: Hypothesis Tests
Unit C: Inference for Means and Proportions
Chapter 5: Approximating with a Distribution
Chapter 6: Inference for Means and Proportions
Unit D: Inference for Multiple Parameters
Chapter 7: Chi-Square Tests for Categorical Variables
Chapter 8: ANOVA for Comparing Means
Chapter 9: Inference for Regression
Chapter 10: Multiple Regression
Optional:
Chapter 11: Probability Basics