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Elementary Statistics With Infotrac,9780534399153
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Elementary Statistics With Infotrac

by
Edition:
9th
ISBN13:

9780534399153

ISBN10:
0534399150
Format:
Hardcover
Pub. Date:
7/1/2003
Publisher(s):
Cengage Learning
List Price: $343.95

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This is the 9th edition with a publication date of 7/1/2003.
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Summary

Part One: DESCRIPTIVE STATISTICS. 1. Statistics. Chapter Case Study. What Is Statistics? Introduction to Basic Terms. Measurability and Variability. Data Collection. Comparison of Probability and Statistics. Statistics and Technology. Chapter Summary. 2. Descriptive Analysis and Presentation of Single-Variable Data. Chapter Case Study. Graphs, Pareto Diagrams, and Stem-and-Leaf Displays. Frequency Distributions and Histograms. Measures of Central Tendency. Measures of Dispersion. Mean and Standard Deviation of Frequency Distribution. Measures of Position. Interpreting and Understanding Standard Deviation. The Art of Statistical Deception. Chapter Summary. 3. Descriptive Analysis and Presentation of Bivariate Data. Chapter Case Study. Bivariate Data. Linear Correlation. Linear Regression. Chapter Summary. Part Two: PROBABILITY. 4. Probability. Chapter Case Study. The Nature of Probability. Probability of Events. Simple Sample Spaces. Rules of Probability. Mutually Exclusive Events and the Addition Rule. Independence, the Multiplication Rule, and Conditional Probability. Combining the Rules of Probability. Chapter Summary. 5. Probability Distributions (Discrete Variables). Chapter Case Study. Random Variables. Probability Distributions of a Discrete Random Variable. Mean and Variance of a Discrete Probability Distribution. The Binomial Probability Distribution. Mean and Standard Deviation of the Binomial Distribution. Chapter Summary. 6. Normal Probability Distributions. Chapter Case Study. Normal Probability Distributions. The Standard Normal Distribution. Applications of Normal Distributions. Notation. Normal Approximation of the Binomial. Chapter Summary. 7. Sample Variability. Chapter Case Study. Sampling Distributions. The Central Limit Theorem. Application of the Central Limit Theorem. Chapter Summary. Part Three: INFERENTIAL STATISTICS. 8. Introduction to Statistical Inferences. Chapter Case Study. The Nature of Estimation. Estimation of Mean ( Known). The Nature of Hypothesis Testing. Hypothesis Test of Mean ( Known): A Probability-Value Approach. Hypothesis test of Mean ( Known): A Classical Approach. Chapter Summary. 9. Inferences Involving One Population. Chapter Case Study. Inferences About Mean ( Unknown). Inferences About the Binomial Probability of Success. Inferences About Variance and Standard Deviation. Chapter Summary. 10. Inferences Involving Two Populations. Chapter Case Study. Independent and Dependent Samples. Inferences Concerning the Mean Difference Using Two Dependent Samples. Inferences Concerning the Difference Between Means Using Two Independent Samples. Inferences Concerning the Difference Between Proportions Using Two Independent Samples. Inferences Concerning the Ratio of Variance Using Two Independent Samples. Chapter Summary. Part Four: MORE INFERENTIAL STATISTICS. 11. Applications of Chi-Square. Chapter Case Study. Chi-Square Statistic. Inferences Concerning Multinomial Experiments. Inferences Concerning Contingency Tables. Chapter Summary. 12. Analysis of Variance. Chapter Case Study. Introduction to the Analysis of Variance Technique. The Logic Behind ANOVA. Applications of Single-Factor ANOVA. Chapter Summary. 13. Linear Correlation and Regression Analysis. Chapter Case Study. Linear Correlation Analysis. Inferences About the Linear Correlation Coefficient. Linear Regression Analysis. Inferences Concerning the Slope of the Regression Line. Confidence Interval Estimates for Regression. Understanding the Relationship Between Correlation and Regression. Chapter Summary. 14. Elements of Nonparametric Statistics. Chapter Case Study. Nonparametric Statistics. Comparing Statistical Tests. The Sign Test. The Mann-Whitney U Test. The Runs Test. Rank Correlation. Chapter Summary. References. Appendix A: Data Sets. Appendix B: Tables. Binomial Probabilities. Probabilities for the Standard Normal Distribution. Critical Values of Students'' t Distribution. Critical values of the Chi-Square Dis

Table of Contents

Descriptive Statistics
Statistics
Americans, Here's Looking At You
What is Statistics? Measurability and Variability
Data Collection
Comparison of Probability and Statistics
Statistics and Technology
Descriptive Analysis and Presentation of Single-Variable Data
You and the Internet
Graphical Presentation of Data
Graphs, Pareto Diagrams, and Stem-And-Leaf Displays
Frequency Distributions and Histograms
Numerical Descriptive Statistics
Measures of Central Tendency
Measures of Dispersion
Measures of Position
Interpreting and Understanding Standard Deviation
The Art of Statistical Deception
Mean and Standard Deviation of Frequency Distribution (Optional)
Descriptive Analysis and Presentation of Bivariate Data
The Kid is All Grown Up
Bivariate Data
Linear Correlation
Linear Regression
Probability
Probability
Sweet Statistics
Probability of Events
Conditional Probability of Events
Rules of Probability
Mutually Exclusive Events
Independent Events
Mutually Exclusive, Independent Events?
A Relationship?
Probability Distributions (Discrete Variables)
Caffeine Drinking
Random Variables
Probability Distribution of a Discrete Random Variable
Mean and Variance of a Discrete Probability Distribution
The Binomial Probability Distribution
Mean and Standard Deviation of the Binomial Distribution
Normal Probability Distributions
Intelligence Scores
Normal Probability Distributions
The Standard Normal Distribution
Applications of Normal Distributions
Notation
Normal Approximation of the Binomial
Sample Variability
275 Million Americans
Sampling Distributions
The Sampling Distribution of Sample Means
Application of the Sampling Distribution of Sample Means
Inferential Statistics
Introduction to Statistical Inferences
Were They Shorter Back Then? The Nature of Estimation
Estimation of a Mean (= known)
The Nature of Hypothesis Testing
Hypothesis Test of Mean 8 (= Known): A Probability Value Approach
Hypothesis Test of Mean 8 (= Known): A Classical Approach
Inferences Involving One Population
Get Enough Daily Exercise? Inferences About Mean 8 (= Unknown)
Inferences About the Binomial Probability of Success
Inferences About Variance and Standard Deviation
Inferences Involving Two Populations
Students, Credit Cards and Debt
Independent and Dependent Samples
Inferences Concerning the Mean Difference Using Two Dependent Samples
Inferences Concerning the Difference Between Means Using Two Independent Samples
Inferences Concerning the Difference Between Proportions Using Two Independent Samples
Inferences Concerning the Ratio of Variances Using Two Independent Samples
More Inferential Statistics
Applications of Chi-Square
Cooling a Great Hot Taste
Chi-Square Statistic
Inferences Concerning Multinomial Experiments
Inferences Concerning Contingency Tables
Analysis of Variance
Time Spent Commuting to Work
Introduction to the Analysis of Variance Technique
The Logic Behind ANOVA
Applications of Single-Factor ANOVA
Linear Correlation and Regression
Beautiful Golden Wheat! Linear Correlation Analysis
Inferences About the Linear Correlation Coefficient
Linear Regression Analysis
Inferences Concerning the Slope of the Regression Line
Confidence Interval Estimates For Regression
Understanding the Relationship Between Correlation and Regression
Elements of Nonparametric Statistics
Teenagers' Attitudes
Nonparametric Statistics
Comparing Statistical Tests
The Sign Test
The Mann-Whitney U Test
The Runs Test
Rank Correlation
Basic Principles of Counting
Tables
Answers to Odd-Numbered Exercises
Answers to Chapter Practice Tests
Index for Applications
Index for Computer and Calculator Instructions
Index Credits
Formula Card
Table of Contents provided by Publisher. All Rights Reserved.


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