Solution Manual for Interactive Statistics (Classic Version), 3rd Edition, Martha Aliaga

This is completed downloadable of Solution Manual for Interactive Statistics (Classic Version), 3rd Edition, Martha Aliaga

Product Details:

• ISBN-10 ‏ : ‎ 0131497561
• ISBN-13 ‏ : ‎ 978-0131497566
• Author: Martha Aliaga

This volume takes a hands-on approach to the introduction of basic statistical methods, using a highly interactive method. Readers are taught to ask “why” and think like a statistician to find the logical solution. With its strong emphasis on data analysis, the book gives readers the skills to understand and interpret a variety of statistical results. Provides an overview of the basic components of decision-making and using statistical ideas. Helps readers master the language of statistics, the importance of a p-value, and the meaning of statistical significance. Includes coverage of current topics such as power of the test and effect size, bootstrap, and blocking designs in experiments. Usesexamples frombusiness, sports, economics, and more to address a wide range of interests. Includes chapter-ending TI Quick Steps for using calculators to enter, manipulate, and plot data. For anyone interested in learning more about statistics.

 

Table of Contents

Note: Each chapter ends with a Chapter Summary, Key Terms, and

Exercises.

Chapter 1: How to Make a Decision with Statistics

Chapter 2: Producing Data

Chapter 3: Observation Studies and Experiments

Chapter 4 Summarizing Data Graphically

Chapter 5 Summarizing Data Numerically

Chapter 6 Using Models to Make Decisions

Chapter 7: How to Measure Uncertainty with Probability

Chapter 8: Sampling Distributions: Measuring the Accuracy of Sample Results

Chapter 9: Making Decisions about a Population Proportion with Confidence

Chapter 10: Making Decisions about a Population Mean with Confidence

Chapter 11: Comparing Two Treatments

Chapter 12: Comparing Many Treatments

Chapter 13: Relationships Between Quantitative Variables

Chapter 14: Analysis of Count Data

Chapter 15: What if the Assumptions Don’t Hold?

 

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