Statistics: Unlocking the Power of Data, 2nd Edition
By Robin H. Lock, Patti Frazer, Kari Lock Morgan, Eric F. Lock, and Dennis F. Lock
Statistics: Unlocking the Power of Data is designed for use as an introductory statistics course. The focus throughout is on data analysis of real data with real applications, and the primary goal is to enable students to effectively collect data, analyze data, and interpret conclusions. Randomization and bootstrap interval methods introduce the fundamental idea of statistical inference, and concepts are brought to life through authentically relevant examples enabled through easy-to-use statistical software.
The next generation of WileyPLUS for Statistics gives instructors the freedom and flexibility to tailor content and easily manage their course to keep students engaged and on track.
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Adaptive practice provides endless opportunities for students to effectively prepare for class or quizzes and exams.
Active retrieval of information with practice questions is proven to improve retention of information better than re-reading or reviewing the material, and students who use adaptive practice to prepare for exams do significantly better than those who do not. Students begin with a quick, section-level diagnostic to determine their initial level of understanding, and they can use the dashboard and quick reports to see what topics they know and don’t know.
Video Lectures build upon concepts covered in class.
Video Lectures provide explanations of key course concepts to enhance the learning experience.
StatKey applets are designed specifically for students using this program.
StatKey Online Interactive Tools are an open source set of applets that are preloaded with the data students will need, and links to StatKey are integrated into WileyPLUS question statements.
- Embedded and Searchable Tables and Figures
- Video Solutions and Tutorials
- Embedded Dataset Index (including links to datasets by page number)
- New and Updated Exercises: This course includes over 300 completely new exercises. In addition to the many new exercises, over 100 exercises have been updated.
- Multiple Variables and Data Visualization: A new section on multiple variables and data visualization is incorporated into Section 2.
- StatKey Enhanced: The online interactive dynamic software has been enhanced, including adding the option to upload whole datasets with multiple variables.
- End-of-Section Essential Synthesis Feature: Integration of the parts of the course into a coherent whole is essential to success. To address this, Essential Synthesis features at the end of each course section ask students to take a step back and look at the big picture. These exercises help to prepare students for the kind of statistical thinking they will most likely encounter after finishing the course.
- The Next Generation of WileyPLUS:
This online tool gives instructors the freedom and flexibility to tailor content and easily manage your course to keep students engaged and on track. - Adaptive Practice: Students begin with a quick, section-level diagnostic to determine their initial level of understanding, and they can use the dashboard and quick reports to see what topics they know and don’t know.
- Adaptive Algebra Refresher Module: An adaptive practice module to master algebra skills provides students with a personalized study plan to master concepts prior to the course, allowing for instructors to focus class time on progression.
Features Include
Statistics Enhancements Include:
Patti Frazer Lock is the Cummings Professor of Mathematics in the department of mathematics, computer science, and statistics at St. Lawrence University. She is a member of the Calculus Consortium for Higher Education (formerly the Calculus Consortium based at Harvard). She is a co-author with the consortium of Texts in Calculus, Applied Calculus, Multivariable Calculus, Precalculus, and Algebra. She is currently working on a text in introductory statistics. She does workshops around the country on the teaching of undergraduate mathematics. She is a member of the Committee on the Undergraduate Program in Mathematics of the Mathematics Association of America, is on the editorial board of PRIMUS Journal and is a consultant to Project NExT of the MAA. She loves to teach courses across the spectrum of mathematics and statistics and enjoys collaborating with undergraduates on her research in graph theory. She received her B.A. from Colgate University and her Ph.D. from the University of Massachusetts at Amherst.
Robin H. Lock is Burry Professor of Statistics in the department of mathematics, computer science, and statistics at St. Lawrence University. He is a fellow of the American Statistical Association, past chair of the Joint MAA-ASA Committee on Teaching Statistics, a member of the committee that developed GAISE (Guidelines for Assessment and Instruction in Statistics Education), and a member of the Consortium for the Advancement of Undergraduate Statistics Education, CAUSE. His work was recognized with the ASA’s inaugural Waller Distinguished Teaching Career Award in 2014 and he has won numerous other awards for presentations on statistics education at national conferences. He brings to the project an insider’s understanding of national trends in statistics education.
Kari Lock Morgan is now an assistant professor in the statistics department at Penn State University after finishing her Ph.D. in statistics at Harvard University and spending three years teaching at Duke University. She has taught a variety of statistics classes, including a special course for graduate students on “The Art and Practice of Teaching Statistics,” and she helped co-develop a new 100-level course at Harvard designed to make statistics enjoyable and applicable to real life. She won the Derek C. Bok Award for Excellence in the Teaching of Undergraduates. She is particularly interested in causal inference, statistics education, and applications of statistics in psychology, education, and health.
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Eric F. Lock is an assistant professor of biostatistics at the University of Minnesota School of Public Health. He received his Ph.D. in statistics from the University of North Carolina in 2012 and spent two years doing a postdoc in statistical genetics at Duke University. He has been an instructor and instructional assistant for multiple introductory statistics courses ranging from very traditional to more progressive. He is particularly interested in machine learning and the analysis of high-dimensional data, and he has conducted research on applications of statistics in genetics and medicine.
Dennis F. Lock recently followed his interests in sports statistics to become the director of analytics for the Miami Dolphins. He finished his Ph.D. focusing on sports statistics with the Department of Statistics at Iowa State University where he served as a statistical consultant for several years and received the Dan Mowrey Consulting Excellence Award. In 2014, he helped design and implement a randomized study at Iowa State to compare the effectiveness of randomization and traditional approaches to teaching introductory statistics.
1. Collecting Data
2. Describing Data
3. Confidence Intervals
4. Hypothesis Tests
5. Approximating with a Distribution
6. Inference for Means and Proportions
7. Chi-Square Tests for Categorical Variables
8. ANOVA to Compare Means
9. Inference for Regression
10. Multiple Regression
P. Probability Basics (flexible section)
A. Section Summaries
B. Select Data Descriptions