Introduction to Statistics and Data Analysis

, by Peck, Roxy; Olsen, Chris; Devore, Jay L.

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ISBN: 9780840054906 | 0840054904
Cover: Hardcover
Copyright: 1/1/2011

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INTRODUCTION TO STATISTICS AND DATA ANALYSIS, 4th Edition, introduces you to the study of statistics and data analysis by using real data and attention-grabbing examples. The authors guide you through an intuition-based learning process that stresses interpretation and communication of statistical information. Simple notation--including the frequent substitution of words for symbols--helps you grasp concepts and cement your comprehension. You'll also find coverage of the graphing calculator as a problem-solving tool, plus hands-on activities in each chapter that allow you to practice statistics firsthand.

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
Collecting Data Sensibly
Statistical Studies: Observation and Experimentation
Sampling
Simple Comparative Experiments
More on Experimental Design
More on Observational Studies: Designing Surveys (Optional)
Interpreting and Communicating the Results of Statistical Analyses
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
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
Summarizing Bivariate Data
Correlation
Linear Regression: Fitting a Line to Bivariate Data
Assessing the Fit of a Line
Nonlinear Relationships and Transformations
Logistic Regression (Optional)
Interpreting and Communicating the Results of Statistical Analyses
Probability
Chance Experiments and Events
Definition of Probability
Basic Properties of Probability
Conditional Probability
Independence
Some General Probability Rules
Estimating Probabilities Empirically Using Simulation
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
Sampling Variability And Sampling Distribution
Statistics and Sampling Variability
The Sampling Distribution of a Sample Mean
The Sampling Distribution of a Sample Proportion
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
Hypothesis Testing Using A Single Sample
Hypotheses and Test Procedures
Errors in Hypotheses Testing
Large-Sample Hypothesis Tests for a Population Proportion
Hypotheses Tests for a Population Mean
Power and Probability of Type II Error
Interpreting and Communicating the Results of Statistical Analyses
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 a Difference Between Two Population or Treatment Proportions
Interpreting and Communicating the Results of Statistical Analyses
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
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 (Optional)
Inferences About the Population Correlation Coefficient (Optional)
Interpreting and Communicating the Results of Statistical Analyses
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)
Activity 14.1: Exploring the Relationship Between Number of Predictors and Sample Size
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)
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
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Introduction to Statistics and Data Analysis

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