Understanding Basic Statistics, International Metric Edition, 8th Edition

Brase/Brase’s UNDERSTANDING BASIC STATISTICS, 8E, INTERNATIONAL METRIC EDITION provides instructors a streamlined and effective way to teach the essentials of statistics, including early coverage of regression, within a more limited timeframe. With simulation questions, labs, projects, news-sourced videos with questions, and more available in the online course, this solution includes an entire course package designed to teach students the basics of statistics and how to apply those to real-world situations. Help your students think statistically, overcome their apprehension about statistics, and learn to love a subject that once inspired anxiety. In this 8th Edition, International Metric Edition, students see the real-world significance of statistics and engage with new features that help them develop critical thinking and statistical literacy skills. The use of the graphing calculator, Microsoft® Excel®, MINITAB®, MINITAB EXPRESS, and SPSS® is covered but not required.

1. GETTING STARTED.
What Is Statistics? Random Samples. Introduction to Experimental Design.
2. ORGANIZING DATA.
Frequency Distributions, Histograms, and Related Topics. Bar Graphs, Circle Graphs, and Time-Series Graphs. Stem-and-Leaf Displays.
3. AVERAGES AND VARIATION.
Measures of Central Tendency: Mode, Median, and Mean. Measures of Variation. Percentiles and Box-and-Whisker Plots.
4. CORRELATION AND REGRESSION.
Scatter Diagrams and Linear Correlation. Linear Regression and the Coefficient of Determination.
5. ELEMENTARY PROBABILITY THEORY.
What Is Probability? Some Probability Rules-Compound Events. Trees and Counting Techniques.
6. THE BINOMIAL DISTRIBUTION AND RELATED TOPICS.
Introduction to Random Variables and Probability Distributions. Binomial Probabilities. Additional Properties of the Binomial Distribution.
7. NORMAL CURVES AND SAMPLING DISTRIBUTIONS.
Part I: Graphs of Normal Probability Distributions. Standard Units and Areas under the Standard Normal Distribution. Areas Under Any Normal Curve. Part II: Sampling Distributions. The Central Limit Theorem. Normal Approximation to Binomial Distribution and to p ̂ Distribution.
8. ESTIMATION.
Estimating µ When σ Is Known. Estimating µ When σ Is Unknown. Estimating p in the Binomial Distribution.
9. HYPOTHESIS TESTING.
Introduction to Statistical Tests. Testing the Mean µ. Testing a Proportion p.
10. INFERENCES ABOUT DIFFERENCES.
Tests Involving Paired Differences (Dependent Samples). Inferences about the Difference of Two Means µ1 − µ2. Inferences about the Difference of Two Proportions p1 − p2.
11. ADDITIONAL TOPICS USING INFERENCE.
Part I: Inferences Using the Chi-Square Distribution.
Overview of the Chi-Square Distribution. Chi-Square: Tests of Independence and of Homogeneity. Chi-Square: Goodness of Fit. Testing a Single Variance or Standard Deviation.
Part II: Inferences Relating to Linear Regression.
Inferences for Correlation and Regression.

• The chapter on Normal Curves and Sampling Distributions (Chapter 7) has been divided into two parts that give appropriate places for pause to review and summarize content. Each part has a brief introduction, brief summary, and list of chapter problems applicable to the part.
• New Terminology problems are included in the chapter problems. These problems are primarily true/false or multiple choice, highlighting some of the main features of terms or concepts.
• Brief discussions of Ethics in statistics (Section 1.3) based on guidelines recommended by the American Statistical Association; Appropriate use of P-values (Section 9.3) as discussed by the American Statistical Association; Data Science and Big Data (Using Technology, Chapter 2)
• Examples, guided exercises, and problem sets have been updated to reflect more recent real data and real-world scenarios.
• Updates in Technology sections include instructions for Excel 2013, Minitab 17, and the new Minitab Express.

• Coverage of the descriptive components of regression early in the text makes it easier to provide students with a thorough introduction to essential statistical concepts, and helps them to steadily build knowledge and improve their skills throughout the course. Inferences regarding regression are in a later section that can be covered after discussion of estimation (Section 8.1, 8.2) and hypothesis testing (Sections 9.1,9.2).
• Critical Thinking boxes at the end of most sections help students hone their critical thinking skills by providing additional clarification on specific statistical concepts as a safeguard against incorrect evaluation of information.
• Interpretation boxes in several chapters help students refine their critical thinking and analysis skills by providing them with practice in explaining their statistical results in the context of a particular application.
• Guided exercises immediately follow selected examples and provide an opportunity for students to explore new concepts. Step-by-step solutions accompanying each exercise allow for immediate self-evaluation and reinforcement.
• "Expand Your Knowledge" problems present the geometric mean and the harmonic mean, moving averages, correlation of averages, odds for and odds against, uniform probability distribution, plus-four methods for confidence intervals, probability of two confidence intervals, and serial correlation.
• Special margin notes draw attention to more information about a related topic that appears in the "Expand Your Knowledge" exercises at the end of the section, allowing you to cover additional material as desired and enabling students to learn more about topics they find especially interesting or difficult to grasp.

Charles Henry Brase
Regis University

Charles Brase has more than 30 years of full-time teaching experience in mathematics and statistics. He taught at the University of Hawaii, Manoa Campus, for several years and at Regis University in Denver, Colorado, for more than 28 years. Charles received the Excellence in Teaching award from the University of Hawaii and the Faculty Member of the Year award from Regis University on two occasions. He earned degrees from the University of Colorado, Boulder, and has a Ph.D. in Mathematics, an M.A. in Mathematics, and a B.A. in Physics.

Corrinne Pellillo Brase
Arapahoe Community College

Corrinne Pellillo Brase has taught at Hawaii Pacific College, Honolulu Community College, and Arapahoe Community College in Littleton, Colorado. She was also involved in the mathematics component of an equal opportunity program at the University of Colorado. Corrinne received the Faculty of the Year award from Arapahoe Community College. She earned degrees from the University of Colorado, Boulder, and has an M.A. and B.A. in Mathematics.