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Mind on Statistics

by ;
Edition:
3rd
ISBN13:

9780495112075

ISBN10:
0495112070
Format:
Hardcover
Pub. Date:
1/3/2006
Publisher(s):
Cengage Learning
List Price: $255.95

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Summary

MIND ON STATISTICS helps you develop a conceptual understanding of statistical ideas and shows you how to find meaning in data. Utts and Heckard explain statistical topics through excellent examples and case studies. This textbook balances the spirit of statistical literacy with the statistical methodology taught in general introductory statistics courses. You'll develop your statistical intuition by focusing on analyzing data and interpreting results, rather than on mathematical formulation.

Table of Contents

Statistics Success Stories and Cautionary Tales
What is Statistics? Seven Statistical Stories with Morals
The Common Elements in the Seven Stories
Turning Data Into Information
Raw Data
Types of Data
Summarizing One or Two Categorical Variables
Finding Information in Quantitative Data
Pictures for Quantitative Data
Numerical Summaries of Quantitative Variables
Bell-Shaped Distributions of Numbers
Gathering Useful Information
Description or Decision? Using Data Wisely
Speaking the Language of Research Studies
Designing a Good Experiment
Designing a Good Observational Study
Difficulties and Disasters in Experiments and Observational Studies
Sampling: Surveys And How To Ask Questions
The Beauty of Sampling
Sampling Methods
Difficulties and Disasters in Sampling
How to Ask Survey Questions
Relationships Between Quantitative Variables
Looking for Patterns With Scatterplots
Describing Linear Patterns With a Regression Line
Measuring Strength and Direction With a Regression Line
Why Answers May Not Make Sense
Correlation Does Not Prove Causation
Relationships Between Categorical Variables
Displaying Relationships Between Categorical Variables
Risk, Relative Risk, Odds Ratio, and Increased Risk
Misleading Statistics About Risk
The Effect of a Third Variable and Simpson?s Paradox
Assessing the Statistical Significance of a 2 x 2 Table
Probability
Random Circumstances
Interpretations of Probability
Probability Definitions and Relationships
Basic Rules for Finding Probabilities
Strategies for Finding Complicated Probabilities
Using Simulation to Estimate Probabilities
Coincidences and Intuitive Judgments About Probability
Random Varaibles
What is a Random Variable? Discrete Random Variables
Expectations for Random Variables
Binomial Random Variables
Continuous Random Variables
Normal Random Variables
Approximating Binominal Distribution Probabilities
Sums, Differences, and Combinations of Random Variables
Means and Proportions as Random Variables
Understanding Dissimilarity Among Samples
Sampling Distributions for Sample Proportions
What to Expect of Sample Means
What to Expect in Other Situations: Central Limit Theorem
Sampling Distribution for Any Statistic
Standardized Statistics
Student?s t-Distribution: Replacing = with s
Statistical Inference
Estimating Proportions With Confidence
The Language and Notation of Estimation
Margin of Error
Confidence Intervals
Calculating a Margin of Error for 95% Confidence
General Theory of Confidence Intervals for a Proportion
Choosing a Sample Size For a Survey
Using Confidence Intervals to Guide Decisions
Testing Hypotheses About Proportions
Formulating Hypothesis Statements
The Logic of Hypothesis Testing: What if the Null is True? Reaching a Conclusion About the Two Hypotheses
Testing Hypotheses About a Proportion
The Role of Sample Size in Statistical Significance
Real Importance versus Statistical Significance
What Can Go Wrong: The Two Types of Errors
More About Confidence Intervals
Examples of Different Estimation Situations
Standard Errors
Approximate 95% Confidence Intervals
General Confidence Intervals for One Mean or Paired Data
General Confidence Intervals for the Difference Between Two Means (Independent Samples)
The Difference Between Two Proportions (Independent Samples)
Understanding Any Confidence Interval
More About Significance Tests
The General Ideas of Significance Testing
Testing Hypotheses About One Mean or Paired Data
Testing the Difference Between Two Means (Independent Samples)
Testing the Difference Between Two Population Proportions
The Relationship Between Significance Tests and Confidence Intervals
The Two Types of Errors and Their Probabilities
Evaluating Significance in Research Reports
More About Regression
Sample and Population Regression Models
Estimating the Standard Deviation for Regression
Inference About the L
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