Introduction to Statistics and Data Analysis
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Introduction to Statistics and Data Analysis

Introduction to Statistics and Data Analysis

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About the Book

This book 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. They help you grasp concepts and cement your comprehension by using simple notation-frequently substituting words for symbols. You will 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.

Table of Contents:
1. THE ROLE OF STATISTICS AND THE DATA ANALYSIS PROCESS. Three Reasons to Study Statistics. The Nature and Role of Variability. Statistics and the Data Analysis Process. Types of Data and Some Simple Graphical Displays. Activity 1.1: Head Sizes: Understanding Variability. Activity 1.2: Estimating Sizes. Activity 1.3: A Meaningful Paragraph. 2. COLLECTING DATA SENSIBLY. Statistical Studies: Observation and Experimentation. Sampling. Simple Comparative Experiments. More on Experimental Design. More on Observational Studies: Designing Surveys (optional). Communicating and Interpreting the Results of Statistical Analyses. Activity 2.1: Designing a Sampling Plan. Activity 2.2: An Experiment to Test for the Stroop Effect. Activity 2.3: McDonalds and the Next 100 Billion Burgers. Activity 2.4: Video Games and Pain Management. Graphing Calculator Explorations. 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. Communicating and Interpreting the Results of Statistical Analyses. Activity 3.1: Locating States. Activity 3.2: Bean Counters! Graphing Calculator Explorations. 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. Communicating and Interpreting the Results of Statistical Analyses. Activity 4.1: Collecting and Summarizing Numerical Data. Activity 4.2: Airline Passenger Weights. Activity 4.3: Boxplot Shapes. Graphing Calculator Explorations. 5. 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). Communicating and Interpreting the Results of Statistical Analyses. Activity 5.1: Exploring Correlation and Regression Technology Activity (Applets). Activity 5.2: Age and Flexibility. Graphing calculator Explorations. 6. PROBABILITY. Chance Experiments and Events. Definition of Probability. Basic Properties of Probability. Conditional Probability. Independence. Some General Probability Rules. Estimating Probabilities Empirically and Using Simulation. Activity 6.1: Kisses. Activity 6.2: A Crisis for European Sports Fans? Activity 6.3: The "Hot Hand" in Basketball. Graphing Calculator Explorations. 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. The Binomial and Geometric Distributions. Normal Distributions. Checking for Normality and Normalizing Transformations. Using the Normal Distribution to Approximate a Discrete Distribution. Activity 7.1: Rotten Eggs. Graphing Calculator Explorations. 8. SAMPLING VARIABILITY AND SAMPLING DISTRIBUTIONS. Statistics and Sampling Variability. The Sampling Distribution of a Sample Mean. The Sampling distribution of a Sample Proportion. Activity 8.1: Do Students Who Take the SAT Multiple Times Have an Advantage in College Admissions? Graphing Calculator Explorations. 9. ESTIMATION USING A SINGLE SAMPLE. Point Estimates. Large-Sample Confidence Interval for a Population Proportion. Confidence Interval for a Population Mean. Communicating and Interpreting the Results of Statistical Analyses. Activity 9.1: Getting a Feel for Confidence Level. Activity 9.2: An Alternative Confidence Interval for a Population Proportion. Graphing Calculator Explorations. 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 the Probability of Type II Error. Communicating and Interpreting the Results of Statistical Analyses. Activity 10.1: Comparing the t and z Distributions. Graphing Calculator Explorations. 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 a Difference Between Two Population or Treatment Proportions. Communicating and Interpreting the Results of Statistical Analyses. Activity 11.1: Helium-Filled Footballs? Activity 11.2: Thinking About Data Collection. Graphing Calculator Explorations. 12. THE ANALYSIS OF CATEGORICAL DATA AND GOODNESS-OF-FIT TESTS. Chi-Square Tests for Univariate Categorical Data. Tests for Homogeneity and Independence in a Two-Way Table. Communicating and Interpreting the Results of Statistical Analyses. Activity 12.1: Pick a Number, Any Number. Activity 12.2: Color and Perceived Taste. Graphing Calculator Explorations. 13. SIMPLE LINEAR REGRESSION AND CORRELATION: INFERENTIAL METHODS. The 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). Communicating and Interpreting the Results of Statistical Analyses. Activity 13.1: Are Tall Women from "Big" Families? Graphing Calculator Explorations. 14. MULTIPLE REGRESSION ANALYSIS. Multiple Regression Models. Fitting a Model and Assessing Its Utility. Inferences Based on an Estimated Model (Online). Variable Selection and Other Issues in Multiple Regression (Online). Communicating and Interpreting the Results of Statistical Analyses (Online). Activity 14.1: Exploring the Relationship Between Number of Predictors and Sample Size. 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). Communicating and Interpreting the Results of Statistical Analysis (Online). Activity 15.1: Exploring Single-Factor ANOVA. Appendix: ANOVA computations (Online). Graphing Calculator Exploration. 16. NONPARAMETRIC STATISTICAL METHODS (ONLINE). Distribution-Free Procedures for Inferences about a Difference Between Two Population or Treatment Means Using Independent Samples (Online). Distribution-Free Procedures for Inferences Concerning a Difference. Between Two Population Means Using Paired Samples (Online). Distribution-Free ANOVA (Online). Appendix: Statistical Tables. Answers to Selected odd-Numbered Exercises. Index.


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Product Details
  • ISBN-13: 9780495118770
  • Publisher: Cengage Learning, Inc
  • Publisher Imprint: Brooks/Cole
  • Height: 251 mm
  • Spine Width: 30 mm
  • Width: 216 mm
  • ISBN-10: 049511877X
  • Publisher Date: 01 Jul 2007
  • Binding: Paperback
  • Language: English
  • Weight: 1600 gr


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