Discovering the Fundamentals of Statistics by Daniel Larose - Second Edition, 2014 from Macmillan Student Store

Discovering the Fundamentals of Statistics

w/EESEE/CrunchIT! Access CardSecond Edition ©2014 Daniel Larose

Discovering the Fundamentals of Statistics by Dan Larose is the ideal brief introductory statistics text that balances the teaching of computational skills with conceptual understanding. Written in a concise, accessible style, Discovering the Fundamentals of Statistics helps stude...
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ISBN:9781464143120

ISBN:9781464127175

ISBN:9781464127182

ISBN:9781464110801

Discovering the Fundamentals of Statistics by Daniel Larose - Second Edition, 2014 from Macmillan Student Store

Discovering the Fundamentals of Statistics by Dan Larose is the ideal brief introductory statistics text that balances the teaching of computational skills with conceptual understanding. Written in a concise, accessible style, Discovering the Fundamentals of Statistics helps students develop the quantitative and analytical tools needed to understand statistics in today’s data-saturated world. Dan Larose presents statistical concepts the way instructors teach and the way students learn.

Features

New to This Edition

Content Updates Based on User Feedback

 “Hypothesis Testing” (Chapter 9) has been rewritten to give instructors the option of teaching the critical-value method only, teaching the p-value method only, or covering both methods.
 
New and revised coverage includes: Revised coverage of group data, revised coverage of applications of the Normal distribution, revised coverage of sampling distributions, revised coverage of inference for two independent means and two independent proportions, new case studies on Worldwide Patterns of Cellphone Usage and Text Messaging 
 
New Pedagogy
Consistent with Larose’s more comprehensive text (see previous page ), the new Discovering the Fundamentals of Statistics includes:

The “Big Picture” highlighting chapter contents at the outset in a bulleted list

“Now You Can Do It” exercises in the margins next to selected example solutions, direct students to exercises at the end of the chapter that require the technique explained in that example.  With this, students can put what they’ve learned into practice immediately.
 
“Bringing It All Together” exercises within each section offer an accumulation of everything students have learned in a particular section, using a related set of Applying the Concepts exercises to tie together the main concepts and techniques learned.
 
Approximately 30% New Examples and Exercises
All examples and exercises come from topics, subject areas, and aspects of everyday experience that students can relate to their own lives.
 
New Technology

StatsPortal now features Freeman’s acclaimed LearningCurve activities (see p. ), approximately 40 new EESEE (Electronic Encyclopedia of Statistical Examples and Exercises) Case Studies, updated StatsTutor tutorials, new assessment-ready applets, CrunchIT! software, and more.
 
CrunchIT!, Freeman’s open-source statistical software, has been added to the “Step-By-Step Technology Guides”

Digital Options

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E-book

Read online (or offline) with all the highlighting and notetaking tools you need to be successful in this course.

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Table of Contents

1. The Nature of Statistics
2. Describing Data Using Graphs and Tables
3. Describing Data Numerically
4. Correlation and Regression
5. Probability
6. Probability Distributions
7. Sampling Distributions
8. Confidence Intervals
9.  Hypothesis Testing
10. Two-Sample Inference
11. Further Inference Methods
 
Additional Chapter:
Nonparametric Statistics (available online and through custom publishing)
 

Daniel T. Larose

Since his days of collecting baseball cards as a youngster, Dan Larose has felt a lifelong passion for statistics. He completed his PhD in statistics from the University of Connecticut in Storrs in 1996. Today, Larose is Professor of Statistics in the Department of Mathematical Sciences at Central Connecticut State University. There, he designed, developed, and directs the world’s first online Master of Science degree in data mining. He has published three books on data mining, and is a consultant in statistics and data mining. His fondest wish is to impart a love of statistics to a new generation. Larose lives in Tolland, Connecticut, with his wife Debra, daughters Chantal and Ravel, and son, Tristan.

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