WebAssign with Corequisite Support for Peck/Olsen/Short's Introduction to Statistics and Data Analysis, Single-Term Instant Access, 6th Edition

Roxy Peck

Copyright 2020
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WebAssign with Corequisite Support for Peck/Olsen/Short's Introduction to Statistics and Data Analysis, Single-Term Instant Access 6th Edition by Roxy Peck

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Overview
Meet the Author
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Overview

WebAssign with Corequisite Support for Peck/Olsen/Short, Introduction to Statistics and Data Analysis, 6th Edition, accelerates your students’ journey to success. Built by educators, WebAssign provides the flexibility to match any corequisite implementation model and empowers you to deliver the right content at the right time for your students. Tailor your course and save time by using prebuilt homework and prerequisite coursepacks, adding in your own questions and content and accessing student and course analytics. Peck, Olsen and Short's INTRODUCTION TO STATISTICS AND DATA ANALYSIS, 6th Edition, lowers the reading level from the previous edition and significantly increases homework scaffolding for difficulty level. In order to get students thinking statistically, this text stresses interpretation and communication of statistical information through hands-on, activity based learning using real data. Prepare your students for success in your course--and their college careers--with this flexible, affordable and high-quality solution. WebAssign helps to address relevant applications, use of technology and conceptual understanding. Use additional material to accompany the text, including news videos per chapter, pre-made Labs, Project Milestones, Simulation Questions by JMP and Concept Questions.

NEW for Fall 2020 - Turn your students into statistical thinkers with the Statistical Analysis and Learning Tool (SALT). SALT is an easy-to-use data analysis tool created with the intro-level student in mind. It contains dynamic graphics and allows students to manipulate data sets in order to visualize statistics and gain a deeper conceptual understanding about the meaning behind data. SALT is built by Cengage, comes integrated in Cengage WebAssign Statistics courses and available to use standalone.

Meet the Authors

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Roxy Peck

Roxy Peck is emerita associate dean of the College of Science and Mathematics and professor of statistics emerita at California Polytechnic State University, San Luis Obispo. As a faculty member at Cal Poly from 1979 until 2009, Dr. Peck served for six years as chair of the statistics department before becoming associate dean, a position she held for 13 years. She received an M.S. in mathematics and a Ph.D. in applied statistics from the University of California, Riverside. Dr. Peck is nationally known in the area of statistics education, and she was presented with the Lifetime Achievement Award in Statistics Education at the U.S. Conference on Teaching Statistics in 2009. In 2003, she received the American Statistical Association’s Founder’s Award, recognizing her contributions to K-12 and undergraduate statistics education. She is a fellow of the American Statistical Association and an elected member of the International Statistics Institute. Dr. Peck served for five years as the chief reader for the Advanced Placement (AP) Statistics Exam and has chaired the American Statistical Association’s Joint Committee with the National Council of Teachers of Mathematics on Curriculum in Statistics and Probability for Grades K-12 and the Section on Statistics Education. In addition to her texts in introductory statistics, Dr. Peck is co-editor of STATISTICAL CASE STUDIES: A COLLABORATION BETWEEN ACADEME AND INDUSTRY and is a member of the editorial board for STATISTICS: A GUIDE TO THE UNKNOWN, 4TH EDITION. Outside of the classroom, she likes to travel and spends her spare time reading mystery novels. Dr. Peck also collects Navajo rugs and travels to Arizona and New Mexico whenever she can find the time.

What's New

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NEW for Fall 2020 - Turn your students into statistical thinkers with the Statistical Analysis and Learning Tool (SALT). SALT is an easy-to-use data analysis tool created with the intro-level student in mind. It contains dynamic graphics and allows students to manipulate data sets in order to visualize statistics and gain a deeper conceptual understanding about the meaning behind data. SALT is built by Cengage, comes integrated in Cengage WebAssign Statistics courses and available to use standalone.

Features

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FLEXIBILITY AT EVERY STEP: You determine the learning path based upon student mastery of prerequisite content with conditional release. Customize the learning experience to meet any learning style and encourage problem solving and critical-thinking skills.
THE RIGHT CONTENT AT THE RIGHT TIME: Time tested, expertly designed content across the corequisite course spectrum fuels deeper learning for all learning styles. Easy course setup simplifies access to all materials in one place--including ebooks, downloadable worksheets, lecture videos and assignments from both the credit and developmental coursework.
IMPROVED ACCESS THROUGH AFFORDABILITY: No more purchasing of multiple course materials--everything is in one place for one low price! Students may also choose to subscribe to Cengage Unlimited to get access to all Cengage courses and textbooks online for one set price.
ASSESSMENTS THAT REINFORCE CONCEPTS: WebAssign provides a variety of question types that include new concept questions, Stats Labs, Project Milestones, Stats in Practice Video questions, end-of-chapter exercises, Master It tutorials, Watch It video support, Video Examples, lecture videos and more.
STEP-BY-STEP EXAMPLES: 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.

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1. THE ROLE OF STATISTICS AND THE DATA ANALYSIS PROCESS.
Why Study Statistics? The Nature and Role of Variability. Statistics and the Data Analysis Process. Types of Data and Some Simple Graphical Displays. Corequisite Support.
2. COLLECTING DATA SENSIBLY.
Statistical Studies: Observation and Experimentation. Sampling. Simple Comparative Experiments. More on Experimental Design. Interpreting and Communicating the Results of Statistical Analyses. More on Observational Studies: Designing Surveys (online). Corequisite Support.
3. GRAPHICAL METHODS FOR DESCRIBING DATA.
Displaying Categorical Data: Comparative Bar Charts and Pie Charts. Displaying Numerical Data: Stem-and-Leaf Displays. Displaying Numerical Data: Frequency Distributions and Histograms. Displaying Bivariate Numerical Data. Interpreting and Communicating the Results of Statistical Analyses. Corequisite Support.
4. NUMERICAL METHODS FOR DESCRIBING DATA.
Describing the Center of a Data Set. Describing Variability in a Data Set. Summarizing a Data Set: Boxplots. Interpreting Center and Variability: Chebyshev’s Rule, the Empirical Rule, and z Scores. Interpreting and Communicating the Results of Statistical Analyses. Corequisite Support.
5. SUMMARIZING BIVARIATE DATA.
Correlation. Linear Regression: Fitting a Line to Bivariate Data. Assessing the Fit of a Line. Nonlinear Relationships and Transformations. Interpreting and Communicating the Results of Statistical Analyses. Logistic Regression (online). Corequisite Support.
6. PROBABILITY.
Chance Experiments and Events. Definition of Probability. Basic Properties of Probability. Conditional Probability. Independence. Some General Probability Rules. Estimating Probabilities Empirically Using Simulation. Corequisite Support.
7. RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS.
Random Variables. Probability Distributions for Discrete Random Variables. Probability Distributions for Continuous Random Variables. Mean and Standard Deviation of a Random Variable. Binomial and Geometric Distributions. Normal Distributions. Checking for Normality and Normalizing Transformations. Using the Normal Distribution to Approximate a Discrete Distribution. Corequisite Support.
8. SAMPLING VARIABILITY AND SAMPLING DISTRIBUTIONS.
Statistics and Sampling Variability. The Sampling Distribution of a Sample Mean. The Sampling Distribution of a Sample Proportion. Corequisite Support.
9. ESTIMATION USING A SINGLE SAMPLE.
Point Estimation. Large-Sample Confidence Interval for a Population Proportion. Confidence Interval for a Population Mean. Interpreting and Communicating the Results of Statistical Analyses. Bootstrap Confidence Intervals for a Population Proportion (optional). Bootstrap Confidence Intervals for a Population Mean (optional). Corequisite Support.
10. HYPOTHESIS TESTING USING A SINGLE SAMPLE.
Hypotheses and Test Procedures. Errors in Hypothesis Testing. Large-Sample Hypothesis Tests for a Population Proportion. Hypothesis Tests for a Population Mean. Power and Probability of Type II Error. Interpreting and Communicating the Results of Statistical Analyses. Exact Binomial Test and Randomization Test for a Population Proportion (optional). Randomization Test for a Population Mean (optional). Corequisite Support.
11. COMPARING TWO POPULATIONS OR TREATMENTS.
Inferences Concerning the Difference Between Two Population or Treatment Means Using Independent Samples. Inferences Concerning the Difference Between Two Population or Treatment Means Using Paired Samples. Large-Sample Inferences Concerning the Difference Between Two Population or Treatment Proportions. Interpreting and Communicating the Results of Statistical Analyses. Randomization-Based Inference for a Difference in Proportions (optional). Randomization-Based Inference for a Difference in Means (optional). Corequisite Support.
12. THE ANALYSIS OF CATEGORICAL DATA AND GOODNESS-OF-FIT TESTS.
Chi-Square Tests for Univariate Data. Tests for Homogeneity and Independence in a Two-way Table. Interpreting and Communicating the Results of Statistical Analyses. Corequisite Support.
13. SIMPLE LINEAR REGRESSION AND CORRELATION: INFERENTIAL METHODS.
Simple Linear Regression Model. Inferences about the Slope of the Population Regression Line. Checking Model Adequacy. Inferences Based on the Estimated Regression Line (online). Inferences About the Population Correlation Coefficient (online). Interpreting and Communicating the Results of Statistical Analyses (online). Corequisite Support.
14. MULTIPLE REGRESSION ANALYSIS.
Multiple Regression Models. Fitting a Model and Assessing Its Utility. Inferences Based on an Estimated Model (online). Other Issues in Multiple Regression (online). Interpreting and Communicating the Results of Statistical Analyses (online). Corequisite Support.
15. ANALYSIS OF VARIANCE.
Single-Factor ANOVA and the F Test. Multiple Comparisons. The F Test for a Randomized Block Experiment (online). Two-Factor ANOVA (online). Interpreting and Communicating the Results of Statistical Analyses (online). Corequisite Support.
16. NONPARAMETRIC (DISTRIBUTION-FREE) STATISTICAL METHODS (ONLINE).
Distribution-Free Procedures for Inferences About a Difference Between Two Population or Treatment Means Using Independent Samples (Optional). Distribution Free Procedures for Inferences About a Difference Between Two Population or Treatment Means Using Paired Samples. Distribution-Free ANOVA. Corequisite Support.

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